How to superpower a clinical trial with PRS

3 min readApr 21


George Busby, Allelica CSO & Co-Founder

Clinical trials are an essential part of the pharmaceutical industry, but they face many challenges. One of the significant obstacles is the high rate of failure, with over 90% of drug candidates that enter clinical trials ultimately failing to gain regulatory approval. The reasons for this are numerous, including safety concerns, lack of efficacy, and issues with study design or execution.

Clinical trials are also notoriously expensive, with drug development costs estimated to be around $2.6 billion per new drug. The failure of a trial due to lack of efficacy or statistical power can result in substantial costs for pharmaceutical companies that have already invested heavily in research and development. Some estimates suggest that a single Phase III trial can cost up to $100 million, making failures a costly setback for the company.

Fortunately, the emergence of polygenic risk scores (PRS) as a biomarker presents a potential solution to some of the primary challenges facing the pharmaceutical industry. PRS can enable pharmaceutical companies to reduce clinical trial costs by more efficiently selecting patients for clinical trials, stratifying patients according to risk, and predicting treatment outcomes. PRS can also help identify new biomarkers for drug development and repurposing of marketed or investigational products.

Optimize clinical trial participant population

Using PRS, pharmaceutical companies can identify individuals who are most likely to benefit from a particular drug, increasing the probability of success in clinical trials, reducing development costs, and speeding up the drug development process.

PRS can also be used to identify individuals who are at higher risk for developing a particular disease or who may be more likely to respond to a specific treatment. This information can be used to recruit participants for clinical trials more efficiently, increasing the chances of generating positive trial data, and cutting costs on less suitable clinical trial participants.

Stratifying patients into subgroups based on their risk of disease or response to treatment is another way in which PRS can help superpower clinical trials. One such approach is prognostic enrichment, which uses PRS to enrich a trial cohort with individuals with patients whose disease is more likely to develop quickly and therefore reduce the overall size of the trial, cutting overall costs. Another concept is that of predictive enrichment, which aims to select individuals who are more likely to have a benefit from the drug being trialled. Stratification therefore enables more targeted and personalized treatment approaches that lead to better outcomes and reducing the overall burden on healthcare systems.

Increase efficiency in drug development

PRS can also help predict the likelihood of a patient responding to a particular treatment or experiencing adverse events. This information can be used to optimize treatment regimens and reduce the risk of adverse events.

Novel biomarkers for diseases, measured through PRS, can also be used to develop more accurate diagnostic tests or monitor disease progression. By predicting the efficacy of existing drugs in specific patient populations and identifying new drug targets, PRS can accelerate drug development and improve the chances of a successful clinical trial.

Finally, PRS can be used for covariate adjustment, accounting for imbalances in patient characteristics between treatment groups that could affect trial outcomes. For example, a PRS for a certain disease mortality can be included as a covariate, allowing for a cleaner estimation of the treatment effect while controlling for mortality unrelated to the treatment measured by the PRS.

Transform the pharmaceutical industry with precision genomics

The use of PRS has the potential to revolutionize the way clinical trials are designed and conducted in the pharmaceutical industry. By enabling more targeted and personalized treatment approaches, PRS can improve patient outcomes, reduce costs, and accelerate drug development. PRS presents a game-changing technology that offers a range of applications across the pharmaceutical drug development pipeline, including patient selection, patient stratification, outcome prediction, biomarker identification, drug development, and covariate adjustment. In conclusion, PRS presents enormous potential for surmounting some of the primary challenges facing the pharmaceutical industry.

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Allelica is a Software Genomics Company developing algorithms and digital tools to accelerate the integration of Polygenic Risk Score in the clinical practice