In silico trials are computer-based simulations of how a drug or disease impacts physiological and clinical outcomes. They can help improve and shorten conventional in-person trials, by testing hypotheses and answering key trial design questions prior to actual patient recruitment.
An increasingly important R&D tool
In silico trials have gained traction as conventional studies become more challenging and expensive to recruit. Personalized medicines require narrow selection criteria, limiting patient numbers, while ethical hurdles often scupper placebo or control arms. In silico trials with virtual patients skirt both obstacles, helping explain why regulators such as the US FDA are encouraging their use.
In silico trials require accurate, detailed models of disease and treatment. They also need “virtual populations” – individual patient data capturing a realistic range of relevant variables. The explosion of medical knowledge, data and analytics has enabled both the modeling and virtual population components of in silico trials to become more sophisticated and precise.
Nova’s mathematical disease models encompass the scientific community’s accumulated data and insights in a transparent, auditable fashion. Its virtual populations can be built with almost limitless size and scope, and even include ‘digital twins’ – exact copies of a given individual – allowing treatment and placebo to be tested in parallel on the same ‘person’.
Jinkō: making trial simulations accessible
Nova’s trial simulation platform jinkō offers an integrated suite of user-friendly applications across the R&D spectrum – from discovery to market access. It allows scientists and clinicians (not just modeling experts) to design, build and test their own models, and run simulations. And since each model component can be traced back to primary source documentation, everything’s fully traceable, and updatable.
Jinkō is designed for full integration into the conventional R&D process. Investigators can test a range of treatment regimens on virtual populations designed to mirror eligible patient groups. The impact of any single variable (in the regimen or in the population) can be studied without the constraints associated with real-world trials.
For example, jinkō allows to build an in silico trial of non-small cell lung cancer patients with KRAS mutations. Different treatment regimens and patient characteristics (such as age, weight or mutation status) are selected and applied to the virtual study.
By adopting the industry standard SBML model storage and communication format, jinkō can access a wide range of existing models to complement its own model library. The platform design encourages collaboration among R&D teams supporting a given project.
Launched in 2021, jinkō is now being used by Big Pharma and Biotech clients across a range of indications. The underlying models have generated impactful results across respiratory and cardiovascular disease, hepatitis B and lung cancer.