The in silico Patient
The in silico Patient for Multiple Myeloma
Gemini, the in silico patient, is the world’s most accurate computer model of multiple myeloma disease progression and drug response. Gemini simulates drug response at the individual patient level, rapidly identifying populations of patient responders and non-responders for clinical trial design. It also predicts optimal combination therapies and generates evidence for line of therapy change and treatment sequence optimization. Using our leading causal AI and simulation technology, REFS, and the largest clinical genomic data set in oncology, CoMMpass from MMRF, the in silico patient reveals the complex system of interactions underlying disease progression and drug mechanisms used to treat multiple myeloma; including proteasome inhibitors, IMIDs, corticosteroids, alkylating agents, anti-SLAMF7, anti-CD38, and others.
Accurate enough to serve as a companion technology platform in the design of clinical trials and the generation of real-world evidence, the in silico patient accelerates the clinical development of new drugs and optimizes the market positioning of newly launched medicines.
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.
Latest News from GNS Healthcare
GNS Healthcare announces launch of Gemini, the in silico patient
Anatomy of Gemini, the in silico Multiple Myeloma Patient
The core model is derived from ~1,000 multiple myeloma patients enrolled in the MMRF CoMMpass patient registry. Patients are followed longitudinally from diagnosis with data collected every three months and tumor samples analyzed at time of recurrence or progression over an eight year period. Data types include clinical outcomes, cytogenics, immunoglobulin profiles, miRNAseq, RNAseq, and whole genome sequencing. Data from other studies, registries, and databases are also being used to create related in silico multiple myeloma patients and to augment the core model.
The multiple myeloma patient data is run through our causal AI and simulation platform, REFS™, to reconstruct the complex interactions underlying disease progression and drug response, filling in the “missing circuitry” of multiple myeloma to accurately predict disease progression and drug response at the individual patient level.
Previous results and validation of the in silico multiple myeloma patient have been presented at numerous conferences including the American Society of Hematology (ASH) and recently published in journals such as Leukemia.