# US 7,610,153 B2 · Multi-drug titration and evaluation

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- Number: US 7,610,153 B2
- Document ID: US7610153B2
- Status: Granted
- Kind: B2
- Application number: 10/467,835
- Filed: 2002-02-13
- Published: 2004-07-08
- Granted: 2009-10-27
- Earliest claimed: 2002-02-13
- Assignees: Virginia Commonwealth University
- Inventors: W. Hans Carter, Jr.; Chris Gennings; Vernon M. Chinchilli; Margaret Shih
- Web page: https://patentgrep.com/patent/US7610153B2

## CPC

- G16H 10/20: for electronic clinical trials or questionnaires
- G16H 20/10: relating to drugs or medications, e.g. for ensuring correct administration to patients
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

Titration of a combination of drugs or treatment modalities within individual subjects is carried out using an evolutionary operation (EVOP) direct-search procedure such as the Nelder-Mead simplex. Desirability functions are incorporated to define the main response of interest and additional responses or constraints. Statistical methodology for determining whether the titrated treatment combination has resulted in an improvement in patient response and for evaluating whether a therapeutic synergism exists is also incorporated. Inferences can be made about the efficacy of the combination or about the individual drugs or treatment modalities that comprise the combination. This approach allows every patient the potential to benefit from the combination under study and permits the consideration of multiple endpoints simultaneously.

## Claims

### Claim 1

A method for titrating a multi-modality therapy regimen in an individual patient, comprising performing multiple times the steps of:
i) providing p modalities to said individual patient in a plurality of dose combinations;
ii) measuring one or more clinical endpoints in said individual patient;
iii) assigning, using a computer, measurements made in said measuring step for each of said one or more clinical endpoints to a desirability function;
iv) combining, using said computer, all desirability functions to obtain a composite desirability function for each of said plurality of dose combinations;
v) associating, using said computer, each composite desirability function with a vertex of a geometric figure, wherein said geometric figure has vertices, and wherein each of said vertices represents one of said plurality of dose combinations;
vi) outputting, using said computer, a next dose combination by applying an evolutionary operation direct search algorithm to said geometric figure; wherein performing steps i)-vi) multiple times constitutes titration of said multi-modality therapy regimen in said individual patient; and wherein results of said method are shown, displayed or represented as a plot, table or geometric representation, which enables a physician or researcher to evaluate and adjust said multi-modality therapy regimen for said individual patient.

### Claim 2 (depends on 1)

The method of claim 1, wherein said next dose combination is generated, using said computer, by the evolutionary operation direct search algorithm moving away from a vertex which represents a least desirable dose combination through dose space to a new location, wherein said new location represents said next dose combination.

### Claim 3 (depends on 1)

The method of claim 1 wherein said multi-modality therapy regimen is used to treat a combined modality therapy-requiring disease or condition selected from the group consisting of cancer, diabetes, asthma, AIDS, and hypertension.

### Claim 4 (depends on 1)

The method of claim 1 wherein said dose combination comprises at least one exposure to radiation.

### Claim 5 (depends on 1)

The method of claim 1 wherein said dose combination comprises at least one exercise regimen.

### Claim 6 (depends on 1)

The method of claim 1 wherein said desirability function is generated from a logistic cumulative distribution function.

### Claim 7 (depends on 1)

The method of claim 1 wherein said composite desirability function is unweighted.

### Claim 8 (depends on 1)

The method of claim 1 wherein said composite desirability function is weighted.

### Claim 9 (depends on 1)

The method of claim 1 wherein method is carried out in a plurality of individual patients.

### Claim 10

A method for titrating a multi-modality therapy regimen in an individual patient, comprising performing multiple times the steps of:
i) providing p modalities to said individual patient in a plurality of dose combinations;
ii) measuring a clinical endpoint in said individual patient;
iii) assigning, using said computer, said measurements obtained in said measuring step to a desirability function;
iv) associating, using said computer, said measurements obtained in said measuring step for said clinical endpoint with a vertex of a geometric figure, wherein said geometric figure has vertices, and wherein each of said vertices represents one of said plurality of dose combinations; and
v) outputting, using said computer, a next dose combination for said individual patient by applying an evolutionary operation direct search algorithm to said geometric figure, and
vi) performing steps i)-v) multiple times, wherein performing steps i)-v) multiple times constitutes titration of said multi-modality therapy regimen in said individual patient; and wherein results of said method are shown, displayed or represented as a plot, table or geometric representation, which enables a physician or researcher to evaluate and adjust said multi-modality therapy regimen for said individual patient.

### Claim 11 (depends on 2)

The method of claim 2 wherein said evolutionary operational direct search algorithm is the Nelder-Mead algorithm, said geometric figure is a simplex, and said number of said plurality of dose combinations is p +1.

### Claim 12 (depends on 10)

The method of claim 10, wherein said next dose combination is generated, using said computer, by the evolutionary operation direct search algorithm moving away from a vertex which represents a least desirable dose combination through dose space to a new location, wherein said new location represents said next dose combination.

### Claim 13 (depends on 12)

The method of claim 12, wherein said evolutionary operational direct search algorithm is the Nelder-Mead algorithm, said geometric figure is a simplex, and said number of said plurality of dose combinations is p +1.

### Claim 14 (depends on 1)

The method of claim 1, further comprising the steps of
performing steps i) through vii) in a plurality of patients;
constructing, using said computer, a confidence ellipsoid about a central location of final dose combinations in p-dimensional dose space; and
evaluating said confidence ellipsoid to determine
whether a combination of p modalitites is better than no treatment at all; or
whether a combination of p modalities is better than a combination of fewer than p modalities.

### Claim 15 (depends on 10)

The method of claim 10, further comprising the steps of
performing said steps of said method in a plurality of patients;
constructing, using said computer, a confidence ellipsoid about a central location of final dose combinations in p-dimensional dose space; and
evaluating said confidence ellipsoid to determine
whether a combination of p modalitites is better than no treatment at all; or
whether a combination of p modalities is better than a combination of fewer than p modalities.

### Claim 16 (depends on 1)

The method of claim 1, further comprising the steps of performing steps i) through vi) in a plurality of patients; and
statistically testing for an improvement in response.

### Claim 17 (depends on 10)

The method of claim 10, further comprising the step of statistically testing for an improvement in response.

### Claim 18

A method for titrating a multi-modality therapy regimen in a plurality of patients, comprising the steps of:
i) providing p modalities to an individual patient in a plurality of dose combinations;
ii) measuring a clinical endpoint in said individual patient;
iii) assigning, using a computer, measurements obtained in said measuring step to a desirability function;
iv) associating, using said computer, said measurements made obtained in said measuring step for said clinical endpoint with a vertex of a geometric figure, wherein said geometric figure has vertices, wherein each of said vertices represents one of said plurality of dose combinations; and
v) determining, using said computer, a next dose combination for said individual patient by applying an evolutionary operation direct search algorithm to said geometric figure, and
vi) performing steps i)-v) multiple times, wherein said step of performing each of said steps constitutes titration of said multi-modality therapy regimen in said individual patient; and wherein results of said method are shown, displayed or represented as a plot, table or geometric representation, which enables a physician or researcher to evaluate and adjust said multi-modality therapy regimen for said individual patient;
vii) performing said steps i)-vi) of said method in each individual in said plurality of patients;
viii) constructing, using said computer, a confidence ellipsoid about a central location of final dose combinations for said plurality of patients in p-dimensional dose space; and ix) evaluating said confidence ellipsoid to determine
whether a combination of p modalitites is better than no treatment at all; or
whether a combination of p modalities is better than a combination of fewer than p modalities.

### Claim 19 (depends on 18)

The method of claim 18 further comprising the step of assigning, using said computer, said measurements obtained in said measuring step to a desirability function prior to associating, using said computer, said measurements with a vertex of said geometric figure.

### Claim 20 (depends on 18)

The method of claim 18, wherein said next dose combination is generated, using said computer, by the evolutionary operation direct search algorithm moving away from a vertex which represents a least desirable dose combination through dose space to a new location, wherein said new location represents said next dose combination.

### Claim 21 (depends on 20)

The method of claim 20, wherein said evolutionary operational direct search algorithm is the Nelder-Mead algorithm, said geometric figure is a simplex, and said number of said plurality of dose combinations is p +1.

### Claim 22 (depends on 18)

The method of claim 18, further comprising the step of statistically testing for an improvement in response.