How can identical twins, with the same genetic makeup, experience different diseases? Scientists believe this is due to epigenetic marks or chemical tags that play a role in controlling the activities of genes. The study of the epigenetic landscape has already generated recent breakthroughs in the detection, treatment and prognosis of many diseases, including cancer.
These breakthroughs are due in part to large-scale mapping efforts of cancer genomes coupled with the rapidly dropping costs of high-throughput next-generation sequencing technologies. Identification of mutations and epigenetic analysis are the next frontier for finding reliable biomarkers and developing targeted therapies.
Next-generation sequencing platforms are particularly powerful for mutational and epigenetic studies due to their ability to quickly analyze the entire genome through multiple methods of sequencing, such as DNA, RNA, miRNA, whole genome, exome, targeted, ChIP-Seq, methylome and epigenome. As a result, researchers obtain comprehensive, clinically relevant data sets.
With these resulting data, computational biologists can mine both open source data sets along with data sets from clinical trials to narrow down options for prospective biomarkers. Continue reading
First established as a standard practice in clinics, in vivo imaging also benefits translational or preclinical research. For the past 25 years, many studies have relied on in vivo imaging as a method to quantify treatment response and gain early insights on efficacy. Now, as the technology advances, researchers can expect to benefit from greater spatial resolution and software advancements that allow faster, cost-effective translation of study results.
Personalized medicine presents a complex technological challenge. Combining an in vitro test for patient diagnosis and selection with a specific drug therapy — each traditionally the product of a separate industrial sector — requires the integration of two somewhat disparate development tracks, as well as all the skills needed to navigate both paths. It is hardly a theoretical conundrum. Short of producing a mass-market blockbuster with unprecedented safety and efficacy, the fate of the typical pharma company may hang on whether it can achieve superior outcomes by using biomarker tests to match new, targeted drugs to the right patients for the best-possible therapeutic management and response. Despite the innate challenge of integrating drug and device development inside traditional pharma companies, personalized medicine has them rushing to develop and commercialize companion diagnostics (CDx) products. 
Successful drug development is increasingly dependent on a robust “fail fast” strategy that includes incorporation of safety / toxicology endpoints into lead optimization pharmacology studies. This early marriage of pharmacology and toxicology will provide insight into the margin of safety that is critical for advancing the molecule, the design of the GLP studies and the clinical plan. Biopharmaceutical companies that employ a “fail fast” strategy can make safety decisions from the integration of toxicology into pharmacology studies, which markedly reduces lead optimization cycle times and overall spend during this phase. 