Software Relating Genes to Disease and Clinical Outcomes

DESCRIPTION (Applicant's abstract): The development of a software system is proposed that will combine statistical theory, computer science algorithms, and genetics expertise to take advantage of the great influx of data generated by both the study of the human genome and the creation of inexpensive genotyping techniques. This software will elucidate the complex relationship between drug efficacy and side effects, and multiple interacting genes and environmental factors. Preliminary results, obtained by using simulated data, indicate that it might be feasible to link phenotype to genotype for a list of "candidate genes." The statistical methods are expected to be successful even if the disease mechanism can differ from one person to another. By analyzing and interpreting clinical trial data, the software will match drugs to target populations according to their specific genotype. This will enable pharmaceutical companies to create novel drugs that render maximum effectiveness and have minimum side effects, i.e. the right drug for the right person. PROPOSED COMMERCIAL APPLICATION: The target markets for the research include pharmaceutical companies, CRO'S universities, and government agencies. It has good potential for commercialization because it is expected to help create novel drugs, boost the safety of drug treatments, save substantial resources, and make sense of complex genotype/phenotype relationships in clinical trials context.