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Gemini –

The in silico Patient™

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Gemini –

The in silico Patient™

Gemini —
The in silico Patient™

Our core solution, Gemini — The in silico Patient™, is a data-driven ensemble of computer models linking drug treatment to patient characteristics to the complex molecular mechanisms and pathways driving clinical outcomes. Gemini simulates disease progression and drug response at the individual patient level to reveal responder vs. non-responder subpopulations and the underlying mechanisms of response. This enables the running of “virtual” or “in silico” head-to-head clinical trials that optimize inclusion/exclusion criteria in trial design and rapidly generate comparative effectiveness evidence.

Using REFS, our patented first-in-class causal AI and simulation technology and cloud-based supercomputers, the complex molecular mechanisms driving outcomes are reverse-engineered from large clinico-genomic patient data to create Gemini in silico patients. Data inputs include DNA sequence variation, gene expression, proteomics, single-cell profiling, immune profiling, labs, clinical outcomes, EMR, and more.

Featured Applications

Like real patients, in silico patients generate insights that are applied throughout the biopharma lifecycle. In addition to clinical trial simulation, simulating gene and protein “knock downs” in Gemini enables the hypothesis-free discovery of novel drug targets and disease mechanisms that can be rapidly validated experimentally. Beyond clinical trial design and drug discovery applications, simulating real world comparative effectiveness in Gemini rapidly generates insights to drive sequence optimization and line of therapy changes. These insights result in better positioning of newly launched therapies with health systems and payers.

Run in silico Head-to-Head Clinical Trials

Create your trial’s in silico comparator arm, making it easy to glean valuable insights from early trial data and simulate how your patient population will respond to a treatment over standard of care therapies, enabling more confident decisions on patients enrollment.


Line of Therapy Optimization

Answer what-if questions such as “what if a patient received Drug X in the first line instead of the standard of care?” Simulate patient response to treatment with an alternate line of therapy using the in silico patient.

Treatment Sequence Optimization

Better understand optimal treatment sequences and address in which order should drugs be delivered. Find where a drug best fits in to the journey of a patient’s care with major implications for market access and commercialization.

Featured Gemini Models

The first model, Gemini — The in silico Patient™ for Multiple Myeloma, launched in early 2020. It is built primarily from the largest clinical genomic data set in oncology, CoMMpass from The Multiple Myeloma Research Foundation, and contains the mechanisms of efficacy of the currently marketed drug therapies.

Subsequent Gemini models in oncology and neurodegeneration are to be released in 2021, with immunology and cardiometabolic disease to follow in 2022.