Precision immunology company Scipher Medicine has unveiled ClinicalTrialRank.com, a breakthrough artificial intelligence platform designed to predict clinical trial failures with unprecedented accuracy. The technology promises to transform drug development by enabling biopharmaceutical companies and investors to avoid investing billions in therapies destined to fail.
The platform represents the culmination of over 10 years of intensive research and technological development by Scipher Medicine's scientific team. Built upon the human interactome—the most comprehensive protein-protein interaction network biology map—the system has developed complex disease models validated by over 100 peer-reviewed published papers.
Revolutionary Predictive Capabilities
ClinicalTrialRank.com employs a sophisticated multi-layered approach that overlays genotype, phenotype, and treatment models onto the interactome. The system systematically learns from the underlying network patterns of approved drugs and patients' therapeutic responses to generate precise rankings of therapeutic targets.
The platform evaluates targets based on two critical factors: their proximity and relevance to disease genetic predisposition, and their ability to revert patients' perturbed molecular profiles to a healthy state. This comprehensive analysis yields accurate target rankings that have demonstrated remarkable predictive power.
Scipher Medicine has applied this technology across approximately 25 diverse disease areas. Through rigorous internal analysis, the company has demonstrated that poorly ranked targets are terminated before market launch nearly 100% of the time. This validation represents approximately 1,000 ceased clinical trials that could have been avoided, potentially redirecting billions of dollars to more promising therapeutic targets.
Addressing Industry-Wide Challenges
"The development model in bio-pharma is broken as too many drugs fail in the clinic. We need to better de-risk at each stage of development," stated Reg Seeto, CEO of Scipher Medicine. "Our commercial test, PrismRA, has already proven the ability to commercially de-risk development by predicting treatment response. PrismRA is the only CMS approved treatment classifier in immunology."
Seeto emphasized the broader impact of the new platform: "With ClinicalTrialRank.com, we are now impacting both pre-clinical and clinical drug development. Our proven ability to predict clinical trial failure combining network medicine, AI and proprietary data, means we enhance the overall probability of clinical development success, especially when clinical failures waste tens of billions of dollars each year."
Scientific Foundation and Mission
The platform's scientific rigor stems from Scipher's foundational work in network biology. Co-founder and network biology pioneer Albert-Laszlo Barabasi, PhD, explained the company's mission: "From the beginning, Scipher's mission has been to ensure patients receive the right drug, eliminating wasteful healthcare spending."
Barabasi continued, "ClinicalTrialRank.com extends this mission to the earliest stages of drug discovery and development, ensuring that the drugs entering the clinic have the highest probability of success. This is not just about financial efficiency; it's about accelerating the delivery of truly effective medicines to patients in need."
Strategic Impact for Industry
The launch of ClinicalTrialRank.com provides biopharmaceutical companies and investors with an essential tool to de-risk development pipelines, optimize research and development portfolios, and allocate capital more effectively. The platform serves as a pivotal resource for companies seeking to mitigate risks within their development pipelines and manage investment capital strategically.
Scipher Medicine leverages AI with network biology and proprietary data through its SPECTRA Rx and Dx platforms, driving the probability of success at each stage of drug development from discovery to commercialization. The company maintains the industry's largest rheumatoid arthritis clinico-genomic data asset and biobank, in addition to electronic medical record data for over 3 million rheumatology patients.
