Field of the invention The invention relates to the field of automating diagnosing patients and clinical trials. More specifically, the invention relates to the use of originally developed clinical algorithms via an expert software system to objectify the diagnosis of patients suffering from Central Nervous System (CNS) related diseases, and for the implementation and analysis of clinical trials in the field of the CNS.

Background of the invention In clinical research, evidence of validity can only start to be gathered when the factors important in distorting an original signal can be identified and teased out in some way. Because of its conceptual complexities the best research in the field of the Central Nervous System (CNS) starts at the level of concepts, but the empirical credibility of biological psychiatry and neurology is threatened by the suspicious validity of its data capture, data processing, data interpreting and data reporting (G.E Berrios and I. S. Markova in Biological Psychiatry, p9 - 2002).

More specifically, diagnoses are made by the use of lists of diagnostic criteria and categories from established classification systems (ICD-10, DSM-IV). The reliability refers to the extent to which clinicians will agree on a specific category as applying to a particular patient. The validity refers to the extent to which the diagnostic category actually reflects specific disease or condition. Making a diagnosis depends on identifying and eliciting the primary clinical data, namely history, symptoms, signs and behaviors. These data will then need to be checked against the list of diagnostic criteria to determine the best fit and hence the most probable diagnosis. However, most diagnostic criteria and categories from established classification systems are not presented in an optimal way. Unfortunately, most psychiatric textbooks and other sources only provide a systematic overview of diseases according to disorder. In order to find out to what disorder best matches certain symptoms, the psychiatrist first needs to have an a priori knowledge about which disorder could cause that symptoms, and, secondly, has to find where exactly these disorders are discussed in the book (or other medium), and whether or not the description of the symptoms findings in this reference text indeed corresponds to his "case". Such a search may be quite straightforward in some cases while it may be quite time-consuming and frustrating in others. Also, even the most recently developed databases on the Internet are organized by disorder, not by symptoms. Furthermore, information in most psychiatry textbooks and other references is not structured according to the work flow of the psychiatrist and finding practical information is difficult. For difficult cases, he has to find an appropriate textbook to identify the diseases that may be present with a pattern similar to the one he has identified. During this process, the psychiatrist creates a list of possible diagnoses (Diagnosis 1 to n), from which the diseases that do not result in the appropriate pattern are eliminated. This list can further be refined by matching the clinical status of his particular patient with the patient-related information provided for the different diseases. It is clearthat this is a quite inefficient process.

Rating scales - often used in the research for new CNS medicaments - are believed to be objective, i.e. valid and reliable with the connotation of scientific, good, above board, not subjective, sellable, better than other approaches, etc., and superior to the happy chat or the clinical interview. There is surprisingly limited evidence for this notion but it survives as a counterpart to the - wrong - view that interviews are subjective. The objective of the rating scale isto measure rapid change in days or weeks. The mystery is why a continuous number can issue out of the arithmetic addition of qualitatt/e decisions.

Global scores are summary narratives and cannot be considered as absolute. A 0 score cannot be interpreted as absence of the condition; nor can someone scoring 40 be said to be twice as sick as someone scoring 20.

The items used in the diagnostic criteria and rating scales are to fulfill a proxy function and the success of any scale depends on the quality of the proxying. Standardization methods cannot evaluate the proxying function of each item. Items do not measure directly the target clinical state, trait or condition; they measure it indirectly, i.e. they are always mediated by a construct. A construct is a notion or image purporting to map or represent something else; it is thus a semantic structure. The semantic information of a scale is found in the instructions and in the history of the scale but the latter two are rarely consulted and pondered over, for there is the wrong belief that once treated statistically, rating instruments become autonomous entities that do not need to have a past.

Conceptual distance is the number of semantic interventions required to convert a phenomenon into an item. The greater the conceptual distance, the more the distortion and/or loss of information. So there is a clear need for minimal or no semantic interventions.

Behavioral phenocopies are represented by the level at which the psychiatric symptoms and signs (data) are being captured by the clinician and hence identified and named. This gives differences in clinical symptoms, signs and behavior that are simply not being determined by the clinician.

Because of the very sensitive process of gathering data throughout CNS clinical trials, there is a need for developing finer phenomenological discriminators.

Detailed description of the invention The present inventors surprisingly found that in CNS trials the very well known low response - in terms of symptom reduction - towards active drugs, in contrast with the experiences in the clinical practice, can be conquered by including only these patients in which there is no important amount of trait symptoms, i.e. symptoms caused by specifications of the personality structure. The reason for this would be that a high trait level causes on the one hand an increased sensitivity to negative feelings (for instance sadness) and an experience of exaggerated negative emotions (for instance guilt) leading to false positive diagnosis (for instance Major Depressive Disorder), and on the other hand an enhanced sensitivity towards attention and support, and low or no sensitivity towards drugs. The present invention thus relates to a method for evaluating drug efficacy in CNS-related disorders, wherein the effects of trait symptoms on the diagnosis are eliminated or at least decreased or reduced. Also, the present invention relates to objectifying diagnosing patients in CNS-related disorders, wherein the effects of trait symptoms on the diagnosis are eliminated or at least decreased or reduced.

The present invention thus relates to a method for evaluating drug efficacy in CNS-related disorders, comprising: (a) providing a patient group diagnosed with a CNS-related disorder, (b) treating a first part of said patient group with a compound to be tested and treating a second part of said patient group with a placebo, (c) diagnosing the State Symptoms of said first and said second patient groups, wherein (the effects of) trait symptoms are eliminated or decreased, (d) comparing the results obtained with said first and said second patient groups from step (c), thereby evaluating drug efficacy.

A further aspect of the invention relates to a method for evaluating drug efficacy in mood disorders, comprising: (a) providing a patient group diagnosed with a mood disorder, (b) treating a first part of said patient group with a compound to be tested (AT) and treating a second part of said patient group with a placebo (PT), (c) diagnosing the State Symptoms (ST) of each individual patient of said first (AT) and said second (PT) patient groups, wherein trait symptoms (TS) are evaluated comprising: (c1) accessing an expert system comprising a database comprising data of symptoms, signs, history, and/or behaviors and disorders associated therewith, (c2) providing data to said expert system on symptoms, signs, history, and/or behaviors of each individual patient of said first (AT) and said second (PT) patient groups, (c2) extracting from the database a list of the severity of the mood disorders corresponding to the symptoms, signs, history, and/or behaviors, wherein trait symptoms are evaluated, (d) comparing the results obtained with said first (AT) and said second (PT) patient groups from step (c), thereby evaluating drug efficacy.

A diminishment of the trait symptoms in the total amount of symptoms in a patient group accentuates the efficacy of an active compound relative to a placebo treated group. For instance, a diminishment of the trait symptoms on the total amount of symptoms in a patient group diagnosed with a depressive state from 50 to 10 per cent, the symptom reduction after 8 weeks of treatment with an active compound would be 18 per cent greater than in the placebo treated group. In comparison, till now the mean difference known by meta-analysis of all the main trials for Major Depressive Disorder is 10 per cent, namely a symptom reduction of 40% in the active treated group and of 30% in the placebo treated group (A. Khan et al, Archives of General Psychiatry, Volume 57, April 20O0).

The following original formula considers the above:

ASR-A8WOT-MDD = ((0.2*%TS)+(0.6*%ST) of AT) - ((0.2*%TS)+(0.4*%ST) of PT),

wherein ASR-A8WOT-MDD stands for Active Symptom Reduction After 8 Weeks Of Treatment; %TS stands for percentage of Trait Symptoms in comparison with the total amount of symptoms; %ST stands for percentage of State Symptoms; AT stands for Active Treatment; and PT stands for Placebo Treatment. Accordingly, the present invention relates to a method for evaluating drug efficacy in CNS- related disorders, comprising determining the Active Symptom Reduction After 8 Weeks Of Treatment (ASR-A8WOT) comprising: (a) providing a patient group diagnosed with a CNS-related disorder, (b) treating a first part of said patient group with a compound to be tested (AT) and treating a second part of said patient group with a placebo (PT), (c1) diagnosing the State Symptoms of said first patient group (ST-i), wherein trait symptoms are evaluated (TS-i), (c2) diagnosing the State Symptoms of said second patient group (ST2), wherein trait symptoms are evaluated (TS2), (d) subtracting the State Symptoms of said second patient group (ST2), wherein trait symptoms are evaluated (TS2) of step (c2), from the State Symptoms of said first patient group (ST1), wherein trait symptoms are evaluated (TS1) from step (d ), thereby evaluating drug efficacy.

Also, the present invention relates to a method as described herein, wherein said method comprises calculating ASR-A8WOT by determining ((0.2*%TS)+(0.6*%ST) of AT) - ((0.2*%TS)+(0.4*%ST) of PT), wherein TS = Trait Symptoms; ST = State Symptoms; AT = Active Treatment; PT = Placebo Treatment

In the present invention, the term "State Symptoms" (ST) relates to these symptoms which define the state of the mentioned disorder, i.e. anhedonia. In the present invention, the term "Trait Symptoms" (TS) relates to these symptoms which define the pre-morbid temperament of the examined person, i.e. novelty seeking, In the present invention, the term "Active Treatment" (AT) relates to a treatment with a substance wherein one or more compound(s) are inserted with demonstrated pharmacological mode(s) of action. In the present invention, the term "Placebo Treatment" (PT) relates to a treatment with a substance wherein no compound(s) is inserted with a demonstrated pharmacological mode of action.

Accordingly, the present invention relates to a method as described herein, wherein said diagnosing the State Symptoms is based on symptom(s), sign(s), history and/or behavior(s).

It will be understood that the method of the present invention relates to diagnosing the State Symptoms by using lists of diagnostic criteria and categories from ICD-10 or DSM-IV. Also, the present invention relates to a method as described herein, wherein said trait symptoms are caused by symptom(s), sign(s), history and/or behavior(s).

Table 1 gives a few examples of the effect towards the Added Symptom Reduction depending on the percentage of trait and state symptoms in a patient group.

The inventor found that the application of this formula can be reached out via an automated checking system ruling originally developed clinical algorithms via an expert software system. As a result, the inventor found that this helps to distinguish those clinical states likely to benefit, for instance, from antidepressant medication from those needing other forms of management.

The terms "treatment", "treating", and the like, as used herein include amelioration or elimination of a developed mental disease or condition once it has been established or alleviation of the characteristic symptoms of such disease or condition. As used herein these terms also encompass, depending on the condition of the patient, preventing the onset of a disease or condition or of symptoms associated with a disease or condition, including reducing the severity of a disease or condition or symptoms associated therewith prior to affliction with said disease or condition. Such prevention or reduction prior to affliction refers to administration of the compound or composition of the invention to a patient that is not at the time of administration afflicted with the disease or condition. "Preventing" also encompasses preventing the recurrence or relapse-prevention of a disease or condition or of symptoms associated therewith, for instance after a period of improvement. It should be clear that mental conditions may be responsible for physical complaints. In this respect, the term "treating" also includes prevention of a physical disease or condition or amelioration or elimination of the developed physical disease or condition once it has been established or alleviation of the characteristic symptoms of such conditions. As used herein, the term "medicament" also encompasses the terms "drug", "therapeutic", "potion" or other terms which are used in the field of medicine to indicate a preparation with therapeutic or prophylactic effect.

The term "diagnosis" is well known in the art and relates to the art or act of recognizing the presence of a disorder from its sign(s), history, behavior(s) and/or symptom(s), and deciding as to its character. A concrete application of such an automated checking system is the clinimetric re- engineering of rating scales used in CNS clinical trials. The principles hereof are the ruling out non-specific complaints and/or symptoms ('noise') and the evaluation of the partial or full resolution of 'core' symptoms of examined disorder by ruling out the trait symptoms in baseline and efficacy evaluation. The term "clinimetrics" is well known in the art, and relates to an accepted method for developing multi-item health measurement rules.

The inventor has developed original procedural re-engineering algorithms for four often used rating scales in the evaluation of the efficacy of psychopharmacological drugs, namely the Hamilton Depression Rating Scale (17 items) (HDRS-17), the Montgommery-Asberg Depression Rating Scale (MADRS), the Young Mania Rating Scale (YMRS), and the Positive and Negative Syndrome Scale (PANSS). For each rating scale algorithms were set out, which, based on the criteria for diagnosis and efficacy of the Diagnostic and Statistical Manual of Mental Disorders, fourth and revised edition (DSM-IV-R) of the American Psychiatric Association (APA), converts the ratings on the different items of the mentioned rating scales into terms of diagnosis and severity of diagnosis and into terms of efficacy, i.e. partial and full response, partial and full remission. The result is a qualitative analysis of the data of the clinical trial, whereas till now there is only a quantitative analysis done. This gives the added value of a drug evaluation, which diminishes the distance between research data and the naturalistic clinical environment in which the drug is meant to be applied. As such, the method of the invention relates not particularly to a subgroup analysis, in which a particular subgroup of patients having a specific parameter is further analysed. Instead, the method of the invention relates to re-analyzing the whole set of data of each individual patient in the patient group. Nonetheless, it will be understood that the methods of the invention may be performed on subgroups of the patient group. In addition, the methods of the invention may also be used to diagnose the most possible disorder based on history, symptoms, signs and behaviors.

Diseases The present invention relates to CNS-related disorders and particularly to mental diseases or disorders which are characterized by an underlying emotion dysregulation. These mental diseases or disorders can be grouped into subclasses as follows: (i) non-cognitive mental disorders comprising mood disorders, anxiety disorders, psychotic disorders, eating disorders, premenstrual syndrome, somatoform disorders , factitious disorders, dissociative disorders, sexual and gender identity disorders, sleep disorders, adjustment disorders, impulse control disorders, pervasive development disorders, attention-deficit disorders, disruptive behavior disorders, substance-related disorders, personality disorders, psychological factors affecting medical conditions, malingering, antisocial behavior, bereavement, occupational problems, identity problem, phase of life problem, academic problem and problems related to abuse or neglect; and (ii) cognitive diseases comprising delirium, Alzheimer Disease, substance-related persisting dementia, vascular dementia, dementia due to HIV disease, dementia due to head trauma, dementia due to Parkinson Disease, dementia due to Huntington Disease, dementia due to Pick Disease, dementia due to Creutzfeldt-Jacob Disease, amnestic disorders due to a general medical condition, substance-induced persisting amnestic disorder, mi Id cognitive impairment disorder, other cognitive disorders.

Accordingly, the present invention relates to a method as described herein, wherein said CNS-related disorder is a mood disorder.

These diseases and their diagnosis are very clearly defined in the "Diagnostic and Statistical Manual of Mental Disorders (DSM-IV)" published by the American Psychiatric Association (http://www.psych.org/). This manual sets forth diagnostic criteria, descriptions and other information to guide the classification and diagnosis of mental disorders and is commonly used in the field of neuropsychiatry. It is for instance available on the internet under: http://www.behavenet.com/ capsules/disorders/ dsm4-tr.htm.

International Classification of Diseases (ICD-10) can be accessed on the internet via: http://www.who.int/classifica1ions/icd/en/.

ICD-10 and DSM-IV are specifically hereby incorporated by reference into the present invention.

Accordingly, the present invention relates to a method as described herein, wherein the severity of the mood disorder is based on the use of I ists of diagnostic criteria and categories from ICD-10 or DSM-IV.

In a further embodiment, the present invention relates to a method as described herein, wherein said lists of diagnostic criteria and categories from ICD-10 or DSM-IV are organized in an expert system, comprising a database. Drug efficacy Accurately matching therapeutic efficacy with biochemical activity is a challenge. The present invention relates to a method of evaluating general therapeutic classes into which various psychoactive drugs fall, based on eliminating or diminishing trait symptoms. The method of the present invention may comprise classification tree and random forest supervised classification algorithms to analyze data. In addition, multiple statistical methods may be applied to classification and recognition of drug efficacy. Supervised classification analysis methods, which can classify patterns of novel data based on prior knowledge of sample classes, include linear discriminant analysis, Fisher discriminant analysis and tree-based analysis.

The efficacy of a drug relates to the capacity or power (strength, effectiveness) of said drug to produce a desired effect. In particular, the ability of a drug to control, cure or ameliorate the effects of a disorder. Efficacy of the present invention includes a Dose/Response efficacy (e.g. in a study to determine a drug's efficacy), a Long Term efficacy (e.g. in a study to determine a drug's efficacy over a longer period of time than had been studied previously) and New indication efficacy (e.g. in a study to determine a drug's efficacy for an indication other than that for which it is currently approved).

The present invention thus relates to a method as described herein, wherein said drug efficacy is evaluated as partial response, full response, partial remission orfull remission.

Expert system The invention also relates to a computer program implementing the method, a database, and a navigation system for extracting or visualizing information from the database. One embodiment of the invention is a method and system for assisting with the diagnosis of a patient, wherein history, symptoms, signs and behaviors are selected from a pre-defined selection. The history, symptoms, signs and behaviors may be chosen from a predefined selection set of history, symptoms, signs and behaviors. The predefined selection may be organized alphabetically, according to type of symptoms, according to the history, according to the signs, according tothe behavior, etc. A hierarchical selection of symptoms starting with broad grouping is within the scope of the invention. For example, the operator may be presented with a broad group of symptom categories from which subgroups may be selected. The limited choice of symptoms enables the operator to clearly describe the disorder, and also provides more precisely defined terms for searching the database. A similar grouping is possible for history, signs and behaviors. The system of the invention may request further input data, whicln may relate also to other patient information such as the sex of patient, age and ethnicity. Such data may be chosen from a predefined list of choices (e.g. sex (MIF), ethnicity (English, Chinese, American, Polish, Indian, Jewish, Asian, South African, Jamaican, etc)). Such limited choice enables the operator clearly to define the other aspects of the patient. Furthermore, the categorization of features also provides more clear terms for searching. Optionally , some input data may be provided as free text description. The input data may also used as input in a database search.

It is an aspect of the invention that the history, symptoms, signs and behavior data are also organized into discrete categories. The categories may be organ ϊzed into hierarchical lists. Each top level category may be subdivided into one or more lower level categories. Such discrete categorization provide the database with a robust structu re, particularly suitable for rapid searching and finding associations. By organizing the input data into discrete categories, the burden of describing the disorder data by the operator of the invention is alleviated. There is no need to use descriptive free text which could otherwise contain « subjective terms not recognized by the database or other operators. Furthermore, categorization allows the database to be searched quickly and accurately, since data therein is already structured into the same discrete categories. Furthermore, the use of discrete categories permits the language or definitions of the input choices to be easily switched. The interface with the operator may be selectable to provide choices such as Latin named categories, English named categories, or a set of synonyms associated with a particular branch of medicine. It also enables the output of the categorized conditions to be provided in a different lexicon. Such flexibility permits the invention to op&rate at different levels of understanding, with experts having different specializations, and in different languages.

Another embodiment of the present invention is a database, comprising data regarding disorders already diagnosed and associated with at least one parameter such as one symptom, one sign, a behavioral pattern or the history of a subject suffering from the disorder. The symptom(s) and other parameters associated with th e disorder are categorized in the database according to a discrete selection of symptoms possibilities. Hierarchical structuring of the categories is within the scope of the invention, as described above. The database thus comprises a structured organization of pre-diag nosed symptoms, history, signs and behaviors and their associated disσders. It is an aspect of the invention that the discrete categories are expandable or contractible according to new methods of diagnosing, new conditions etc.

According to an aspect of the invention, the database further comprises information in respect of conditions already diagnosed in a subject suffering from the condition. Such information may be in the form of discrete categories (e.g. sex, race, age) or numerical or textual, non-categorisable information

According to an aspect of the invention, each criterion, such as symptom, sign, history and behavior may be assigned a numerical value based on diagnostic DSM-IV criteria, for instance as exemplified in the examples section.

A further aspect of the present invention is an expert system as described herein, wherein the data on symptoms, signs, history, and/or behaviors is provided in a numerical value.

For instance, based on diagnostic DSM-IV A and B criteria of the manic episode and converted scores on the YMRS items, Mania Response & Remission System or MRRS may be re-engineered as follows: •crit. A1 (elevated mood) = (i1>2) *crit. A2 (expansive mood) = (i8 >3 or i3>2) •crit. A3 (irritable mood ) = (i5>3) •crit. B1 (grandiosity) = (i8>5) •crit. B2 (decreased need for sleep) = (i4>2) •crit. B3 (talkativeness) = (i6>5) «crit. B4 (racing thoughts) = (i7>1) •crit. B5 (distractibiliy) = (i7>1) •crit. B6 (increase in goal-directed activity or agitation) = (i2>2 or i3=>2 or i8>3) •crit. B7 (excessive involvement in pleasurable activities) = (i1=4 or i3=4)

Accordingly, the present invention relates to a method for evaluating drug efficacy in CNS- related disorders, comprising: (a) providing a patient group diagnosed with a CNS-related disorder, (b) treating a first part of said patient group with a compound to be tested and treating a second part of said patient group with a placebo, and (c) evaluation of the efficacy of said drug by using a re-engineered HDRS-17, MADRS, YMRS or PANSS rating scale.

In a further aspect, the present invention relates to a method for evaluating drug efficacy in CNS-related disorders as described herein, wherein the re-engineered HDRS-17 comprises: •crit. A1 (depressed mood) = i1>0 •crit. A2 (markedly diminished interest) = i7 >1 •crit. A3 (decrease in appetite or weight ) = (i12>0 or i16>0) •crit. A4 (insomnia) = (i4>1 or i5>1 or i6>1 ) -crit. A5 (psychomotor agitation or retardation) = (i8>0 or i9>0) •crit. A6 (fatigue or loss of energy) = i13>1 •crit. A7 (excessive guilt) = i2>1 •crit. A8 (diminished cognitive abilty) = i8>0 •crit. A9 (recurrent thoughts of death, suicidal symptoms) = i3>0, and #crit. C (significant distress or functional impairment) = i7>0

In a further aspect, the present invention relates to a method for evaluating drug efficacy in CNS-related disorders as described herein, wherein the re-engineered YMRS comprises: •crit. A1 (elevated mood) = (i1>2) *crit. A2 (expansive mood) = (i8 >3 or i3>2) •crit. A3 (irritable mood ) = (i5>3) •crit. B1 (grandiosity) = (i8>5) •crit. B2 (decreased need for sleep) = (i4>2) •crit. B3 (talkativeness) = (i6>5) -crit. B4 (racing thoughts) = (i7>1) •crit. B5 (distractibility) = (i7>1) •crit. B6 (increase in goal-directed activity or agitation) = (i2>2 or i3>2 or i8>3), and •crit. B7 (excessive involvement in pleasurable activities) = (i1=4 or i3=4)

In a further aspect, the present invention relates to a method for evaluating drug efficacy in CNS-related disorders as described herein, wherein the re-engineered MADRS comprises: •crit. A1 (depressed mood) = i1>1 or i2>1 •crit. A2 (markedly diminished interest) = i8>1 •crit. A3 (decrease in appetite or weight ) = i5>2 *crit. A4 (insomnia) = i4>2 •crit. A5 (psychomotor agitation or retardation) = i7>1 •crit. A6 (fatigue or loss of energy) = i7>3 •crit. A7 (excessive guilt) = i9>4 •crit. A8 (diminished cognitive abilty) = i6>2 *crit. A9 (recurrent thoughts of death, suicidal symptoms) = i10>1, and •crit. C (significant distress or functional impairment) = i7>1 In a further aspect, the present invention relates to a method for evaluating drug efficacy in CNS-related disorders as described herein, wherein the re-engineered PANSS comprises: all the DSM-IV A-criteria of SCHIZOPHRENIA with: -crit. A1 (DELUSIONS) = i1>3 (all) or i5>4 (grandiose) or i6>3 (persecutory) •crit. A2 (HALLUCINATIONS) = i3>3 •crit. A3 (DISORGANIZED SPEECH ) = i2>3 •crit. A4 (GROSSLY DISORGANIZED OR CATATONIC BEHAVIOR) = ( i4>4 or i7>3) (disorganized behaviσ) or i19>2 (catatonic posturing) or i21>3 (catatonic stupor) or i22>3 (catatonic negativism) •crit. A5 (NEGATIVE SYMPTOMS) = (i8>3 or i9>3 or i10>3) (affective flattening) or i13>2 (alogia) or i27>2 (avolition); and the B-criterion and the 'BIZARRE'-condition of the DSM-IV A-criterion of SCHIZOPHRENIA with: • crit. B (SOCIAL / OCCUPATIONAL DYSFUNCTION)= i11 >2 • BIZARRE DELUSIONS = ( i1>3 or i5>4 or i6>3) and i23>3, and AF1 : Cognitive impairment = i12>3 or i14>2 or i24>2 or i25>2 AF2: Somatic concern = M5>2 AF3: Tension & Anxiety = i18>3 or i16>2 AF4: Depression = i20>2 AF5: Lack of insight = i26>3 AF6: Preoccupation = i29>3 NS1: Pathological guilt feelings = i17>4 NS2: Poor impulse control = i28>3, and NS3: Avoidance = i30>2 , wherein AF is associated features, and NS is non-specific features.

Database A database of the invention comprises all possible combinations of symptoms and further parameters to which specific attributes and more detailed information are attached. Not all combinations of any two of parameters result in a valid combination - for instance, no data for a particular combination may be known. Means for organising data in databases and database management system are known in the art and any are within the scope of the invention. The parameters in a database is at least 2, and may be 3, 4, 5, 6, 7, 8, 9, 10 or more than 10. The number of parameters can be variable and optimised for all combinations of histories, symptom(s), sign(s), behavior(s) and/or condition(s). When the operator of the invention identifies a symptom, sign and/or behavior, the invention is capable of providing a set of possible disorders. This first step of knowing the symptom(s), signs and/or behavior(s) is similar to the actual working practice of the psychiatrist. However, under prior art, the psychiatrist would have to read all available documentation and find out whether there's a matching disorder for each possible symptom, sign and/or behavior. It is not until the information has been read by the psychiatrist that the disorder can be classed. The time spent on reading irrelevant documentation corresponds to lost time. The use of a database of the invention immediately narrows the choices for the operator.

Accordingly, the present invention relates to an expert system for evaluating drug efficacy in CNS-related disorders, comprising: (a) a database comprising data of symptoms, signs, history, and/or behaviors and disorders associated therewith, (b) means for inputting data by an operator of symptoms, signs, history, and/or behaviors of individual patients, (c) accessing means to said database, (d) clinimetric rules for setting a diagnosis, (e) rating scale algorithm for setting a diagnosis, and (f) means for extracting said diagnosis, whereby the drug efficacy is evaluated.

According to an embodiment of the invention, an operator provides the method or system with his choice of symptoms, signs and/or behaviors, and initiates a search of the database, which returns a list of conditions. The search is performed by extracting data from an intersection of the symptoms, signs and/or behaviors crossed by the disorder. The data is extracted along the disorder or condition axis.

A further advantage of the database is evident where simultaneous searching is performed of more than one disorder. Once the operator has selected the symptom(s), sign(s) and/or behavior(s) of the disorder, the search is proceeded by extracting disorder data from intersections of the symptom(s), sign(s) and/or behavior(s) planes crossed by the symptom(s), sign(s) and/or behavior(s) of the disorders. The disorders which are common to the symptom(s), sign(s) and/or behavioφ), as well as disorders attributed to the each symptom, sign and behavior are rapidly provided. This feature is helpful in cases of rare conditions that present atypical symptom, sign and/or behavior manifestations, and in which the combination of findings may provide a clue to the correct diagnosis. Using conventional methods, such diagnosiswould require extensive cross-referencing of medical literature.

The database may provide additional relationships for the sex of patient, age, ethnicity, and the like. The input data permits relationships between for example, ethnicity or age and the likely condition, to be determined. The input data may assist with ranking the diagnoses according to probability. For example, if it is known that there is a predisposition to a type of disorder, such information may be used to increase the probability indication of the disorder. The probability might be presented as a percentage, fraction, or be used to adjust the placing of the condition in an ordered list, for example.

The input data may also be used to request further information from the operator. For example, where input data has not been provided by the operator, and the database indicates a relationship between a likely disorder and a further parameter such as age, for example, the system or method may request this information. Such information may be used to change the probability indication of the disorder. The use of further input data significantly improves the speed and accuracy of the diagnosis. The generation of long lists of possible diagnoses is avoided; normally such lists have to be refined by the operator and depends on the knowledge and experience of the operator. The use of predefined input data allows precise questionsto be formulated by the invention and provides focused diagnoses.

Ranking information is based on the frequency that a particular combination is encountered in practice, for a given combination of symptoms. According to an aspect of the invention, a default frequency may be provided. Exceptions to this default frequency are explicitly stored, together with the combination of the symptoms for which this exception occurs. The default rankings and exceptions may be defined by experts during the data entry process, based on their own experience and available literature data.

An embodiment of the present invention is a database comprising medically defined disorders, wherein at least one dimension is provided for each symptom, sign, behavior and history. As is understood in the art, the relational links between symptom(s), sign(s), history and/or behavior(s) with disorders are provided in the database, so that the data can be represented and searched across data planes and intersections.

Additional information such as age, sex and ethnicity may further influence the ranking of the diagnoses, and may even eliminate some diagnoses from the list. Alternatively, if the database indicates that ranking may depend on for example, age, the invention may prompt the operator to enter such relevant information. There from, the probably or ranking of the disease can be established by the invention. As previously discussed, the invention allows multiple symptoms to be specified, and may automatically assign a higher ranking to those disorders shared by the given symptom(s), sign(s) and/or behavior(s). Such diagnosis may also be given a ranking according any correlation between the patient data in respect of age, sex and symptom(s), sign(s) and/or behavior(s), as mentioned above.

According to an aspect of the invention, the database is not updated with continued use by the operator. Instead, the database information is provided only by experts, and is validated The invention can also be used as a reference medium, comparable to the classical printed or online books. The operator has the possibility to browse the collected information, optionally according to symptom, condition or disorder. Furthermore, the invention may be provided with a search engine, allowing the user to quickly find a particular item of interest, be it a symptom, condition, sign, behavior, disorder, or other content.

Symptom/disorder discriminative value A further aspect of the invention is the use of a discriminative value for the combination of history, symptom(s), sign(s) and/or behavior(s) and disorders. Such value indicates to the method and system whether for the given history, symptom, sign and/or behavior, a history, symptom, sign and/or behavior is discriminative between disorders or is not, respectively. Such value is based on the proven significance of the history, symptom(s), sign(s) and/or behavior(s) in making a diagnosis. If the operator unknowingly identifies a history, symptom(s), sign(s) and/or behavior(s), which has low discriminative value, he might receive the message that this history, symptom(s), sign(s) and/or behavior(s) has a low discriminative value. The invention may then suggest a better approach. Alternatively, the invention may provide a list of diagnoses, in which the discriminative value is used as a factor to order the list by probability. Thus, by adding a discriminative value to the history, symptom(s), sign(s) and/or behavior(s) parameter, a more accurate assistance with diagnosis is achieved. The database may thus comprise the discriminative value as a further feature of the combined history, symptom(s), sign(s) and/or behavior(s) parameter. The discriminative value of a history, symptom(s), sign(s) and/or behavioφ) for a particular disorder may be provided by the expert, and possibly be based on the criteria set out in DSM-IV as mentioned above.

A system of the invention may be one or more devices comprising at least one microprocessor capable of performing a method of the invention. The system may comprise at least one or two networked computers. The operator of the invention may be a specialist or a non-specialist in the field of study. An example of an operator of the invention is a psychiatrist or a specialist in for example, psychology, or other practitioner for whom interpretation of symptoms is necessary.

In a further embodiment, the present invention relates to an expert system as described herein, wherein said expert system groups and evaluates data of patient groups.

In an another embodiment, the present invention relates to an expert system as described herein, wherein said expert system groups and evaluates data of a patient group treated with a placebo andOr a patient group treated with a compound to be tested.

Workflow of the invention Confronted with a history, symptom(s), sign(s) and/or behavior(s), an operator of the invention identifies the most possible disorder connected with said history, symptom(s), sign(s) and/or behaviors). All possible relevant combinations of history, symptom(s), sign(s) and/or behaviors) and disorders are available in the database. The operator just has to identify and select the appropriate history, symptom(s), sign(s) and/or behaviors). As a result, he is given a focused set of diagnoses. Information on the likelihood of each diagnosis for this particular combination of history, symptom(s), sign(s) and/or behavior(s) is also given. For some combinations of history, symptom(s), sign(s) and/or behavior(s), the system may indicate that additional input is required. Input of this additional (patient-related) information by the user results in an optimised ranking of the different disorders for that particular patient.

Compared to the currently available reference material, being a printed or online reference book, the operator does not have to carry the burden of reading lists of diagnoses, history, symptom(s), sign(s) and/or behavior(s), and other material that is irrelevant to the current case.

Furthermore, contrary to advanced types of reference material, such as search engines, the operator does not need to enter specific search criteria, that already assume a fixed idea about the resulting diagnosis. Instead, the system allows the operator to restrict himself to information that is readily available, and to postpone the interpretation to a later stage. Integration According to one aspect of the invention, the method or system is integrated within other systems, such as those with which the operator may already be familiar. It is an aspect of the invention that the method, system and/or database has means to be integrated in these applications to which the operator may already be familiar.

According to one embodiment of the invention, the method or system is provided with a number of standardized services and interfaces, that will allow the invention to be integrated with other applications. For example, an external application may send a message, containing the request, to the invention implemented as a computer program. The invention may respond with a message containing the result. Such message can be captured by the external application, and processed accordingly.

It is another aspect of the invention that the method is executed using a remote computer. Such arrangement permits remote requests to be processed, for example, over the internet, using a network and a central server, or any other remote/central server configuration.

It is also an aspect of the invention that the method may be integrated locally by providing a local instance of the content database and corresponding interfaces.

Speech Integration According to another aspect of the invention, the invention is capable of communicating with an operator using speech or sounds. For example, the invention may recognize a vocabulary, and may be able to respond to the user. It may, for instance ask for more input, or provide the results of a particular operation.

Such speech integration may incorporate control and output of the operator's usual application, depending on the speech capabilities of this type of application. Such integration would result in a complete speech enabled work flow, so increasing the efficiency of the operator.

Lexical and Semantic Layers As mentioned above, the vocabulary used in a certain medical area often contains several synonyms and different terminologies, while the data available in a content database often only contains a subset of the available vocabulary. An operator may not be able to understand the terms available for input or provided by an output, or may want to use a more familiar vocabulary. According to an aspect of the invention, the invention incorporates the use of one or more lexicons. Such lexicons or semantic sources may be built-in or available as "plugs-ins", or as a file of translations, or any other means available to the skilled person. It is an aspect of the invention that such lexicon can be expanded bythe operator, and/or that an operator can create their own vocabulary, and link it to the application. Such lexicon provides an advantage that search items can be compared with the available lexicons and semantic libraries. The method may then optimise the search criteria, and use the results from this lexical and semantic comparison as input for the search operation, in order to capture all relevant data. The output may also be translated according to the understanding of the operator. This lexical layer integration is particularly useful for the more classical approach of the search engine.

External Resources According to an aspect of the invention, the method of the invention may be capable of using data from sources other than the database. If such external resources are available, the invention may be linked to these resources to extend the information. Such external resources include conventional databases and multidimensional databases. It goes without saying that the external sources should be subject to the highest quality criteria. Therefore, a validation of external sources is preferable, and it is even more preferable that external sources are certified. The availability of external sources provides additional flexibility and extensibility to the invention. The invention may thus provide a central integration point for several databases, each built up by a independent providers or partners.

Input/Output Technologies It is an aspect that the invention is capable of supporting at least one printed format and/or electronic display devices in order to indicate the diagnosis. Output may be provided in a non-interactive or interactive format. Non-interactive formats include the printed form as a book, brochure, or other paper formats. Other examples of non-interactive formats are static electronic information, such as a collection of linked HTML or XML pages, or using other publishing technologies, such as pdf (Portable Document Format). The number of available formats being unlimited; the data can always be converted into the appropriate format.

Interactive formats include the system being integrated in the end user's medical information system such as a EMR (Electronic Medical Rscord). The operator may interact with the invention using an interface. The interface may be incorporated into a web browser page, a proprietary interface, an interface generated using a database authoring tool etc. The devices providing at least the interface include a mobile phone, a PDA device, an organiser, a desktop computer, a terminal, a networked computer, a system comprising a microprocessor, an input device and a display device.

The application of these interactive formats is not limited by the output device. For the most common types of electronic devices, an application may be provided that offers a view to the system. These applications may be further speech enabled. A non-visual, speech enabled application can also be provided as a means to interact with the system.

The present invention thus connotes an expert system as described herein, wherein said expert system provides a feedback means to the operator inputting data.

Static database content may be installed locally. Provisions of sufficient disk space to store the content database are known to the skilled person.

On the other hand, static content may be made available via a web server. Provisions of networking (e.g. wired or wireless connection to an intranet or Internet, use of a web browser capable of working with the standard transfer protocols http and https etc) are known to the skilled person.

Dynamic, interactive content may be made available by the invention. Such dynamic content may be provided by way of a connection to the intranet or Internet, and the use of a web browser capable of working with the standard transfer protocols http and https.

According to an aspect of the invention, a method or system is capable of providing an interface for the purpose of browsing data from the database. It may comprise means for extracting data according to the searching requests of the browsing user. The interface may permit graphical one, two or three dimensional representations of data, and means for the browsing userto navigate there through.

The system may be capable of providing a primarily textual online book edition of the database as mentioned below. The system may be provided with a search engine allowing the user to specify a number of search criteria. The result set is presented to him, so he can interactively browse any of the results. This engine may be integrated with a Speech Recognition engine to aid the end user in entering the search criteria.

According to another embodiment, the user may be guided by a number of discriminative questions about the problem area which leads to a reduced set of answers, very closely related to the problem. Again, speech recognitbn may help the end user in answering the necessary questions.

It will be understood that the present invention relates to a computer program on a computer readable medium capable of performing a method as described herein. Also, the present invention relates to a computer program on a computer readable medium capable of providing functionality of a system as described herein. In a further embodiment, the present invention relates to a computer program on a computer readable medium capable of providing a database comprising data of symptoms, signs, history, and/or behaviors and disorders associated therewith.

Data Entry Data Entry Process As mentioned above, a database of the invention comprises all possible combinations of histories, symptom(s), sign(s), behaviors) and/or conditions and disorders to which specific attributes and more detailed information may be attached. According to an aspect of the invention, the content is provided by a group of experts in disorders related to the CNS, that might include, for example psychiatrists, assisted by medical doctors having specialised knowledge about particular disorder. To provide the highest quality, one or more experts from each disorder may provide information to and/or validate the database.

A problem with existing systems is that data entry is subjective and can depend on the understanding and language of the operator. Such variation between operators can lead to incorrect entries in the database. To solve this problem, the inventors have designed an interactive data entry application which guides the data entry operator. Such guidance may be by asking questions to the operator, the use of choice buttons, pull down menus, used such to limit and make consistent the input of the operator. By using such application, the content is entered in a consistent form, and the reuse of pre-existing data is maximized. According to an aspect of the present invention, an interactive data entry application is organized according to the natural work flow, and to the natural relations between the entities in the database. The data entry operator identifies the location, optionally sub location, pattern, disease, or a combination thereof. The data entry user may add characteristic information towards any type of entity encountered. This characteristic information is divided into several categories, which further enhances the search capabilities ofthe invention.

The characteristic information can consist of short descriptions, long descriptions, figures, with or without captions. Additionally, references to official publications, if applicable, are stored together with the corresponding data. According to an aspect of the invention, the categories are configurable. If, at a certain moment, the operator is required to provide an additional characteristic, such characteristic may be added to the system.

To increase the productivity of the data entry users, the data entry application may be speech enabled. Additional interfaces may be provided for import of data in several structured formats (e.g. comma separated text, spreadsheets, XML documents). This interface may extend the solution to also input third party data or data from remote data entry users.

Validation and Approval It is an aspect of the invention the system is configured to prevent data being published, either interactively or non-interactively, without specific approval of dedicated Validation users and Approvers. Validation users and Approvers may be different from the data entry users who are responsible for entering the bulk of the data into the database.

Such configuration may allow every data item to be checked before it is released as publishable data. To increase the productivity, the user responsible for validation and/or approval of the data, may be presented a list of non-validated modifications.

Navigation system One aspect of the invention is a system for navigating a medical database as mentioned herein. The system comprises a means for accessing a database, a means for inputting navigational information, and means for extracting from the database a list of conditions, history, symptom, sign, behavior and disorders, depending on the navigatbnal information.

The system may provide navigation tools including interactive displays which make use of alphanumerical characters and graphics to represent the data. The information contained within the system can be browsed along several axes, depending on the known input parameters. The most natural work flow is to provide input about the history, symptom, sign, behavior and/or condition, but the system will also allow to be browsed as an encyclopaedia for information related to history, symptom, sign, behavior and conditions in case the disorder is known.

According to an aspect of the invention, a navigation system comprises means to providing results of navigation as one or more of text, numbers, case examples, drawings, computer generated graphics, video clips, or any other type of relevant output. The methods or systems of the invention may be provided as a computer program held on a computer readable medium, said program comprising computer code for performing the steps of the method or for providing the functionality of the system. Examples of media include an optical disk, tape, magnetic disk, solid-state memory, hard-drive. The program or system may be available for download across a network. According to one aspect of the invention a method or system is implemented into a stand-alone system, for example, as a package on a desktop computer with a screen and input device, on a laptop computer, on a PDA etc. One embodiment of the invention is a device capable of performing a method of the invention. According to one aspect of the invention the database may be present on a remote server and a program present on a networked local computer to provide an operator with an interface for interacting with the database. Such interface may by provided by known technologies, for example, displayed in a web page, a proprietary interface, an interface generated using an authoring tool etc.

The invention includes any technology which permits the operator to interact with the invention. According to one aspect of the invention, the invention is capable of displaying a web page on a remote computer. Said web page permits the operator to use the invention. It is an aspect of the invention that the use of the method or system by the operator is recorded by the invention for the purpose of billing the operator or his employer. Such billing systems are known in the art. For example, the invention may provide each operator with an account which is charged according to the use of the invention. Such charging may be according to time, the number of searches, complexity of searched, volume of data transfer, or by license with privilege options, etc.

Another aspect of the invention is a database product as described above. The database is preferably curated by a team of experts in history, symptom(s), sign(s), behavior(s) and/or conditions recognition. As already mentioned above the database comprises at least two parameters, with history, symptom(s), sign(s), condition(s) and/or behavior(s) vis a vis disorders data. Further input data comprising the sex of patient, age, ethnicity, and psychological antecedents, for example, may be provided in additional parameters. The database comprises all possible combinations of history, symptom(s), sign(s), behavior(s) and/or conditions and disorders to which specific attributes and more detailed information are attached.

According to an aspect of the invention, a database product is capable of providing or interacting with an interface for the purpose of browsing data from the database. The interface may comprise means for extracting data according to the searching requests of the browsing user. The interface may permit graphical one, two or three dimensional representations of data, and means for the browsing user to navigate there through. The database may be capable of providing a primarily textual online book edition of the database as mentioned below.

The database product may be provided with a search engine allowing the user to specify a number of search criteria. The result set is presented to him, so he can interactively browse any of the results. This engine may be integrated with a Speech Recognition engine to aid the end user in entering the search criteria.

According to another embodiment, the database user may be guided by a number of discriminative questions about the problem area which leads to a reduced set of answers, very closely related to the problem. Again, speech recognition may help the end user in answering the necessary questions.

One embodiment of the invention is a device comprising the database product or capable of accessing the database product.

The features of the database product mentioned above are not limited to the database product, but may also be integrated to the system or method of the invention.

The database product may be provided as a computer program held on a computer readable medium. Examples of media include an optical disk, tape, magnetic disk, solid-state memory, hard-drive. The database program or system may be available for download across a network. It may be available under licenseor pay-per-use. The present invention closely follows the natural work flow of the psychiatrist or medical specialist. Contrary to the current state-of-the-art, the invention allows a considerable reduction in the need for manual intervention, by making an automatic pre-selection based on a number of well-known measurable parameters. As such, the invention facilitates and improves psychiatrist work flow, i.e. the extraction of relevant information from symptoms.

The invention is structured around a relationship between symptom(s), condition(s) and disorder(s), and shows further dimensions according to case specific parameters such as age, sex, etc. This allows a business intelligence like approach to a content database.

The use of symptom(s) as one of the primary navigation axes, offers completely new insight in medical reference material.

Furthermore, the introduction of a ranking of symptom(s) and condition(s) for a particular set of input parameters helps to objectify and thus to increase the quality of the diagnoses, for instance by eliminating and/or reducing trait symptoms. Similarly, the present invention helps to objectify and increase the assessment of clinical trials of compounds by eliminating and/or reducing trait symptoms. It will be understood by the person skilled in the art that the present invention assists in studies of the incidence and distribution of a disorder in a population, and the use thereof to find the causes, modes of transmission, and methods for control of disease (e.g. in epidemiologist).

Importantly, the invention enables the user to obtain relevant information after having identified some basic parameters such as symptom(s) and condition(s). As such, the invention covers process that enables the transformation of symptom(s), sign(s), history, behavior(s) and condition(s) to diagnoses, and the technical structure of the system is irrelevant to the operator.

Throughout this disclosure, various publications, patents and published patent specifications are referenced by an identifying citation. The disclosures of these publications, patents and published patent specifications are hereby incorporated by reference into the present disclosure to describe more fully the state of the art to which this invention pertains. While the present invention will now be described by way of specific examples for the benefit of those in the field, the scope of the invention isonly limited by the appended claims. FIGURES Figure 1A: Efficacy on week 8 of test compound X in MDD (MADRS). Figure 1B: MADRS: baseline distribution. Figure 1C: MADRS total score at baseline. Figure 1 D: Difference of MADRS total score at week 8. Figure 1E: MADRS total score at week 8. Figure 1 F: Remission (MADRS total score at baseline ≤ 10)(%) at week 8. Figure 1G: Qualitative partial remission (%) at week 8. Figure 2: Screen print showing interface produced by a customized application of the NECT built up via decision trees. Figure 3: Screen print showing interface produced by a customized application of the NECT built up via decision trees. Figure 4: Screen print showing interface produced by a customized application of the NECT built up via decision trees. EXAMPLES

EXAMPLE 1: Re-engineering of the Young Mania Rating Scale (YMRS). An example of such a re-engineering isthe Mania Response & Remission System or MRRS.

This re-engineering is based on the fact that all the d iagnosfc DSM-IV A and B criteria of the Manic Episode canbe ruled out by converting the scores on the YMRS items, namely :

•crit. A1 (elevated mood) = (i1>2) -crit. A2 (expansive mood) = (i8 >3 or i3>2) •crit. A3 (irritable mood ) = (i5>3) •crit. B1 (grandiosity) = (i8>5) •crit. B2 (decreased need for sleep) = (i4>2) •crit. B3 (talkativeness) = (i6>5) »crit. B4 (racing thoughts) = (i7>1) •crit. B5 (distractibility) = (i7>1) •crit. B6 (increase in goal-directed activity or agitation) = (i2>2 or i3>2 or i8>3) •crit. B7 (excessive involvement in pleasurable activities) = (i1=4 or i3=4)

The severity of diagnosis can be ruled saying that the> features of 'extreme increase in activity or impairment in judgment' equals to (i2=4 or i11=4), and 'the presence of either delusions or hallucinations or the need to protect the individual fo r harm to self or others' equals to (i8=8 or i9=8).

EXAMPLE 2: Re-engineering of the Study 'Double-Blind Flexible Dose Comparison of the Efficacy and Safety of a test compound and Placebo in the Treatment of Major Depressive Disorder'

Another example of such a re-engineering is the Dep ression Response & Remission System or DRRS.

Subject Qualitative analysis of the data of the study 'Double-Blind Flexible Dose Comparison of the Efficacy and Safety of the test compound and Placebo in the Treatment of Major Depressive Disorder'.

Context There was introduced a new method to re-analyze clinical trials based on clinical algorithms. To deliver proof/no proof of the added value of the test compound - an NMDA receptor antagonist that blocks pathologically increased glutamatergic neurotransmission - i treatment of Major Depressive Disorder, a re-engineering of the results of an existing POC trial was proposed.

Objective By applying the original developed algorithms on the data, additional qualitative information will give new insides. To know if further trials would be reasonable to implement is the key objective. The results will assist in decision making for further research.

Method The scores on the different items of the Montgomery Asberg Depression Rating Scale (MADRS) - as primary outcome - and the Hamilton Depression Rating Scale-17 items (HAMD-17) - as secondary outcome - will be converted in a qualitative way to the DRRS (Depression Response & Remission System).

This re-engineering is based on the fact that all the diagnostic DSM-IV A-criteria and the B- criterion of the Major Depressive Episode (MDE) can be ruled out by converting the scores on the HDRS-17 or the MADRS items, namely for the HDRS-17: •crit. A1 (depressed mood) = i1>0 -crit. A2 (markedly diminished interest) = i7 >1 •crit. A3 (decrease in appetite or weight ) = (i12>0 or i"16>0) •crit. A4 (insomnia) = (i4>1 or i5>1 or i6>1) •crit. A5 (psychomotor agitation or retardation) = (i8>0 or i9>0) •crit. A6 (fatigue or loss of energy) = i13>1 'crit. A7 (excessive guilt) = i2>1 •crit. A8 (diminished cognitive ability) = i8>0 •crit. A9 (recurrent thoughts of death, suicidal symptoms) = i3>0 •crit. C (significant distress or functional impairment) = i7>0

For the HDRS-17, the severity of diagnosis can be ruled saying that the feature 'no disability with unusual effort' equals to item 7 = 1 ,'mild disability' equals to item T = 2 and 'clear-cut, observable disability' equals to item 7 > 2 based on the DSM-IV-R definitions of severity of MDE: MILD MDE = 5 or 6 A-criteria and no disability with unusual effort (LJE) or mild disability (MD) • MODERATE MDE = - 5 or 6 A-criteria and clear-cut, observable disability (DIS) - or 7 or more A-criteria and no disability with unusual effort or mild disability SEVERE MDE = 7 or more A-criteria and clear-cut, observable disabil ϊty

Also for the HDRS-17 the different psychiatric functional states can be ruled saying that the state: • EUTHYMIA = -NO DEPRESSED MOOD = (M=O) and -NO LOST OF INTERESTS = (i7<2) and -NO TEDIUM VITAE = (i3=0) • NL. SOCIAL FUNCTIONING = (i7=0)

For the MADRS this gives: •crit. A1 (depressed mood) = i1>1 or i2==-1 •crit. A2 (markedly diminished interest) = i8>1 -crit. A3 (decrease in appetite or weight ) = i5>2 •crit. A4 (insomnia) = i4>2 •crit. A5 (psychomotor agitation or retardation) = i7>1 •crit. A6 (fatigue or loss of energy) = i7>3 •crit. A7 (excessive guilt) = i9>4 *crit. A8 (diminished cognitive ability) = i6>2 •crit. A9 (recurrent thoughts of death, suicidal symptoms) = i10>1 •crit. C (significant distress or functional impairment) = i7>1

For the MADRS the severity of diagnosis can be ruled saying that the "feature 'no disability with unusual effort' equals to item 7 = 2 or 3, 'mild disability' equals to item 7 = 4, and 'clear- cut, observable disability' equals to item 7 > 4.

Also for the MADRS the different psychiatric functional states can be ruled saying that the state:

• EUTHYMIA = -NO DEPRESSED MOOD = (iK2) and (i2<2) and -NO LOST OF INTERESTS = (iδ<2) and -NO TEDIUM VITAE = (i10<2) • NL FUNCTIONING = (i7<2)

The rules concerning response are also based on the DSM-IV criteria saying:

- PARTIAL RESPONS = diminishment of severity namely 'Severe to moderate •And moderate to mild

- FULL RESPONS = diminishment of severity namely •Severe to mild and -Moderate to mild with 5A and mild interference (unusual effort)

- PARTIAL REMISSION = symptoms still present but full C or A-criteria a re no longer met. This is translated in the rule: ((item 7 = 0 (for the HDRS-17) and item 7 < 2 (for the MADRS) and > 0 A-criteria are fulfilled)) or (1 till 4 A-criteria are fulfilled). - FULL REMISSION = no significant symptoms of MDD = all A-criteria + C-criterion are not fulfilled. Results With DRRS the right patients for the trial can be selected, or the noise can be reduced. The consequence is the evidence for the efficacy of compound X in the treatment of Major Depressive Disorder.

The included patients (135 PLC / 135 X) were selected on the DSM-IV criteria for major depressive disorder ("PLC" = placebo, "X" = test compound).

Relevant parameters of the study are provided in Figures 1 B to 1 G. Figure 1B provides MADRS: baseline distribution. Figure 1 C provides MADRS total score at baseline. Figure 1D provides the difference MADRS total score at week 8. Figure 1E provides MADRS total score at week 8. Figure 1 F provides remission (MADRS total score at baseline <10)(%) at week 8. Figure 1G provides the qualitative partial remission (%) at week 8.

DRRS showed that for the MADRS 157 (58%) of the randomised patients were "no correct baseline" patients (59,7% PLC / 56,6% X): - No valid DSM-IV diagnosis at baseline (n = 76 with 39,6% in the PLC and 35,3% in the X group), Early placebo response (partial or full response, partial or full remission) at baseline (n = 81) More details are provided in Table 2.

For the HAMD-17, 128 (47,5%) of the randomized patients were "no correct baseline" patients (43,9% PLC / 50,0% X): No valid DSM-IV diagnosis at baseline (n = 52 with 18,2% in the PLC and 25,7% in the X group), - Early placebo response at baseline (n = 76). More details are provided in Table 3.

Because of this very large amount of not eligible patients and since there was a margi nally significant difference between X and placebo, favoring placebo, on the mean change from Baseline at end point on the MADRS total score (-10.1 PLC vs. -9.7), the question was raised if there would be a significant difference favoring X by including only the right baseline patients with a moderate to severe severity.

DRRS proved that X is not substantially more effective than placebo in the treatment of Major Depressive Disorder since it leads after 8 weeks of treatment (ITT / LOCF), in the Subgroup of "right baseline patients" with a moderate to severe severity, to less remission not only on quantitative terms (MADRS total score <=10) (3,6% X versus 11 ,5% PLC) but even on the qualitative clinical term of 'partial remission with euthymia' as set out in the algorithms of the DRRS (3,6% X versus 11 ,5% PLC) although there was no difference in both treatment groups on the baseline MADRS total score (33,8 X versus 35,2 PLA). The following Table 4 and also the more detailed data file 'Result All PARAMETERS Re-Eng Study X', which can be found in Tables 5 to 16, show these data very clearly.

Concerning the HAMD-17 scores we can make the same conclusion, i.e. we do not see any difference between Placebo and X regardless of the parameter used.

Conclusion A subgroup analysis in a population of patients with a clinically moderate to severe depression who showed no placebo-response in the placebo run-in phase confirmed the main analysis of this study, with X not being superior to placebo treatment. The main results of the re-analysis in this population are shown in Figure 1A.

As one can see the qualitative result shows that the examined compound has absolutely no effect towards the targeted disorder of Major Depressive Disorder since 'treatment' with this drug gives less moderate to severe depressed patients with a resolution of their diagnosis (Ae. partial remission) or depressed state (Ae. partial remission with euthymia) than the placebo treated patients although the total score of the used rating scale was at week 8 equal for both groups. It can be concluded that X was not effective in the treatment of Major Depressive Disorder.

EXAMPLE 3: Re-engineering of the Positive And Negative Syndrome Scale (PANSS). Another example of such an re-engineering is the Schizophrenia Response & Remission System or SRRS. This is based on the fact that:

1 ) All the DSM-IV A-criteria of SCHIZOPHRENIA can be ruled out via the PANSS namely: •crit. A1 (DELUSIONS) = i1 >3 (all) or i5>4 (grandiose) or i6>3 (persecutory) •crit. A2 (HALLUCINATIONS) = i3>3 •crit. A3 (DISORGANIZED SPEECH ) = i2>3 •crit. A4 (GROSSLY DISORGANIZED OR CATATONIC BEHAVIOR) = ( i4>4 or i7>3) (disorganized behavior) or i19>2 (catatonic posturing) or i21 >3 (catatonic stupor) or i22>3 (catatonic negativism) •crit. A5 (NEGATIVE SYMPTOMS) = (iδ>3 or i9>3 or M0>3) (affective flattening) or i13>2 (alogia) or i27>2 (avolition)

2) The B-criterion and the 'BIZARRE'-condition of the DSM-IV A-criterion of SCHIZOPHRENIA can be ruled out via the PANSS namely: • crit. B (SOCIAL / OCCUPATIONAL DYSFUNCTION)= i11 >2 • BIZARRE DELUSIONS = ( i1>3 or i5>4 or i6>3) and i23>3

3) All the other PANSS items stand for the DSM-IV associated (AF) or non-specific (NS) features of schizophrenia namely: AF1 : Cognitive impairment = i12>3 or ι14>2 or ι24>2 or ι25>2 AF2: Somatic concern = i15>2 AF3: Tension & Anxiety = i18>3 or i16>2 AF4: Depression = i20>2 AF5: Lack of insight = i26>3 AF6: Preoccupation = i29>3 NS1 : Pathological guilt feelings = i17>4 NS2: Poor impulse control = i28>3 NS3: Avoidance = i30>2

The severity of diagnosis of schizophrenia can be ruled saying that the feature:

• motor immobility = (i21=6) • excessive motor activity = (i4=6) • extreme negativism = (i22=6) • mutism = (i13=6) • peculiarities of voluntary movement = (i19>2) • echolalia or echopraxia = (i19=6)

Also for schizophrenia the different attenuated/residual positive criteria (RPS) can be ruled saying that: •crit. A1 (DELUSIONS) = (i1=2,3) (undifferentiated) or (i5=3,4) (grandiose) or (i6=2,3) (persecutory) •crit. A2 (HALLUCINATIONS) = ([3=1 ,2) •crit. A3 (DISORGANIZED SPEECH ) = (i2=2,3) •crit. A4 (GROSSLY DISORGANIZED OR CATATONIC BEHAVIOR) = ( i4=2,3,4) or (i7=2,3) (disorganized behavior) or (i19=1 ,2) (catatonic posturing) or (121=2,3) (catatonic stupor) or (i22=2,3) (catatonic negativism)

The different schizophrenic subsyndroms can be ruled saying that: • POSITIVE SYNDROM = A1 or A2 • DISORGANISED THOUGHTS & SPEECH SYNDROM = A3 • UNCONTROLLED HOSTILITY / EXCITEMENT SYNDROM = (i4>3 or i7>3) • CATATONIC SYNDROM = (M 9>2 or i21 >3 or i22>3) • NEGATIVE SYNDROM = A5

At last the residual negative symptoms can be ruled out by saying that: (iδ=2,3) or (i9=2,3) or (i10=2,3) or (i13=2) or (i27=2).

EXAMPLE 4: Neuronal Electronic Clinical Trial or NECT An example of the use of procedural algorithms in real time is the expert system development called Neuronal Electronic Clinical Trial or NECT. Hereby the inventor developed an electronic data capturing system via electronic item-windows grouped in relevant clinical decision tables, intelligently presented via forward and backward chaining techniques which leads to a semi - mandatory data collection and a real time data control and explanation. The inserted electronic data analysis gives via item related computer algorithms in real time an objective fulfilling of all the, in the clinical trial defined, clinical criteria and measurements.

Via a rigorous integration of decision trees there is presented a simultaneous measurement of DSM-IV rules for diagnosis and efficacy and rating scale scores, per item and total.

The following screen prints (Figures 2 to 4) show the interface produced by a customized application of the NECT built up via decision trees. Table 1

Table 2: overview MADRS study

Table 3: overview H AM D- 17 study

Table 4: overview MADRS

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