In the context of healthcare and treatment therapies for complex diseases the next emerging paradigm shift is move towards personalised medicine. Drug discovery and healthcare orientation will accordingly need to transition beyond the "one size fits-all" methodology. While equality of all is guaranteed in the constitution of most countries; when it comes to drug research and therapeutic regimen determination, it should not necessarily be treated as equals.

Every individual has a unique genetic signature and profile, which may or may not be relevant in the context of a particular disease and drug therapy situation. Based on this profile; the efficacy and related toxicity associated with any drug regimen may vary considerably. Based on expressed genes in an individual the corresponding proteins get transcribed determining the functionality of particular molecular pathways implying uniqueness of individuals. Mutations in genes and proteins may result in over-expression of proteins; absence of proteins or change in functionality of the protein making the understanding of implications of genetic signature variation very challenging.

One disease area in which personalised medicine approach is critical and poised to become almost mandatory component is oncology related therapeutics. Personalised medicine adoption is dependent on the following two key components. Diagnostic ability to determine genetic signature is key to analyze and determine patient specific therapeutic solutions. These genetic profiles can help identify not only patient specific individuality and also assist in identification of disease progression. For genetic profiling to be done in the case of oncology; tumour tissue samples is extracted from the patient followed by different histo-pathological and molecular biology tests to identify the desired genetic markers. Based on identification of these genetic markers; the next step is analysis to determine drug regimen which is appropriate in the context of the patient and disease.

The challenging part is which genetic markers are relevant and to check for and post that how to interpret it in context of disease condition and corresponding drug options. This analysis should give some insight for a specific genetic signature profile whether a particular phenotype or molecular endpoint gets impacted by the drug synergistically or in an antagonistic way. For such an analysis to be done is needed a dynamic physiologically aligned system which is transparent and can be manipulated for various "what-if" analysis. Since the drug mechanism of action is at the bio-molecular level; the dynamic analysis has to be at the bio-molecular abstraction level with all the disease relevant pathways of proteins opened up. Dynamic system specifically refers to an integrated system, which includes representation of the functional relationship between the different biological players. Traditional in vitro and in vivo animal studies do not provide such a transparency and flexibility of analysis besides the fact that these systems do not represent human in vivo physiology.

Such an insight can be made available through the use of in silico based approach and technology. In silico based approach provides a system, which is a transparent view of the bio-molecular pathways relevant to a disease and aligned with human physiology. Such a system approach is based on deployment of in silico disease physiology platform for hypothesis testing in conjunction with traditional omics; in vitro and in vivo approaches. The in silico platform is an integrated and transparent functional view of the disease relevant physiological processes at the biochemical pathway abstraction level. Such a platform map is a library of physiological pathways which can be googled, queried and predictive analysis performed for understanding physiology and coming up with targeted solutions. The over arching objective here is to transition to a personalized molecular targeted solution approach and move away from "trial and error approaches" based on detection and identification of novel bio markers to aid this overall process.

Personalised medicine based approach has already been adopted by the industry and shown early successes. Genentech's drug Herceptin for breast cancer indication is effective in patients with HER2 gene overexpressed. Gleevec from Novartis which is molecular targeted approach to cancer therapy, are indicated for the treatment of patients with protein bcr-abl and or CD117 or c-kit positive. These initial industry success stories in personalised medicine are based on genetic profile testing of specific genes and follow up treatment. Going forward with more drug discovery methodology moving towards molecularly targeted approaches; custom solutions based on genetic profile will definitely get more sophisticated and complex. In such a scenario different cancer phenotypes like survival, metastasis, proliferation, angiogenesis and resistance would need to be analyzed with and without drug with various mutations like PTEN, p53, RAS and EGFR.

So what are the implications of the personalised approach for drug clinical trial companies? The biggest benefit is targeted inclusion and exclusion selection criteria for patients in the clinical studies. Traditionally when drug does not show corresponding efficacy when moving from animals to human clinical studies; one common option is expansion of trials by adding more patients resulting in increase in costs and time to market. Also for these genetic profile tests; patient biopsy samples would be needed which the clinical trial organizations will need to plan for.

With the learning and experiences we have from development approaches and deployment of cancer therapies till date; it is very obvious that an improvement beyond the conventional brute force approaches and "trial and error" approaches is strongly needed. The big opportunity going forward is to inculcate bio-molecular focused solutions based on complete understanding of the disease cause and related physiology. Cancer is an example of a complex disease, which will require a sequential and combinatorial strategy approach in conjunction with ongoing Research & Development in novel signposts or bio-markers. Adoption of in silico approach in drug discovery and research provides a window of opportunity for successfully making this transition to personalised medicine.

(The author is Co-founder and CEO, Cellworks Group Inc.)