Mitigate the risk of efficacy-related clinical failure
Phase II efficacy-related clinical trial failure rates can be as high as 57%, driving pharmaceutical companies on a quest to improve outcomes. As clinical trials become more complex and costly, optimized study designs that take drug candidate efficacy and efficacy precedents into account are an essential part of risk mitigation.
Help to improve early clinical trial success rates
The PharmaPendium Efficacy Module provides essential insights that help to improve early clinical trial success rates. Efficacy data extracted from FDA and EMA drug approval documents provide preclinical and clinical researchers with critical information to better address suboptimal study designs, inappropriate endpoints or poor efficacy. The Efficacy Module makes it easier to:
- Support clinical programs with comparative drug efficacy data
- Optimize drug candidate selection against efficacy benchmarks
- Mitigate the risk of suboptimal clinical trial designs
Avoid suboptimal clinical trial designs
Thorough analyses of successful clinical trial parameters can help inform study designs for drug candidates of similar drugs—saving time and providing additional evidence for regulatory reviews. Additional parameters can also be examined, providing comprehensive and thorough analyses to support clinical study design decisions. Parameters include:
- primary and secondary endpoints,
- sample size by clinical trial phase
- Placebo effects
- Dose regimens
- Confidence metrics
In this figure, the inner circle represents the various parametersthat could potentially lead to late-stage failures. The outside boxes identifies how thePharmaPendium Efficacy Module can provide insights to each of these so researcherscan make better more informed decisions.
Support clinical development with comparative drug efficacy data
View and export comparative efficacy data for entire drug classes, target classes, indications or endpoints in just minutes, saving valuable research time. The Efficacy Module answers complex questions on study parameters that contribute to early clinical failures, such as indication, endpoints and sample size. With unique, normalized taxonomies, it’s possible to find precise information, even when the parameter is described differently in different sources and studies.
Optimize drug candidate selection against efficacy benchmarks
Researchers can leverage comparative clinical data for similar drugs to determine if the selected translational models have the potential to anticipate human outcomes. The Efficacy Module enables the leverage of detailed correlated human and preclinical efficacy data to design more informative studies that can help determine if drug candidates can reach efficacy benchmarks. This knowledge aids in drug candidate selection decisions so only those with the most promising profiles move forward.
Find relevant information fast
Ultimately, the Efficacy Module data structure and taxonomies allow researchers to retrieve comparative information on drugs, target classes, indications or endpoints . Efficacy-based filters drill down to precise information, with categories including sample size, placebo effects and dose regimens. No other resource permits such a quick yet insightful view of detailed information on study designs.