The startup has developed a drug and risk analysis platform that utilizes a mechanistic model of human physiology to simulate metabolic interactions at the cellular level across all tissues. This technology enables researchers to generate causal hypotheses for drug efficacy and systemic toxicity, enhancing the predictability of drug development outcomes.
Funding
Funding not disclosed
HFounders
Product
Problem
Drug discovery faces challenges in predicting drug efficacy and toxicity due to the complexity of cellular mechanisms and the limitations of traditional preclinical assays, which often yield conflicting results and lack detailed mechanistic explanations. This lack of understanding contributes to high failure rates in clinical trials, particularly in potency and toxicity assessments.
Solution
Syntensor offers a platform that simulates complex mechanistic interactions following small molecule perturbation to predict drug efficacy and toxicity. By taking a dynamical systems view of the cell, the platform generates mechanistic, causal hypotheses for drug behavior given a specific cell line and compound. The platform leverages predictive models trained on multi-omics and experimental data to simulate cellular assays at scale and contextualize assay outcomes with predicted genome-wide changes in gene expression levels for novel compounds across cell lines. This enables researchers to understand how perturbing the primary target of the drug leads to changes in the state of the cell, facilitating a more informed assay strategy and anticipating potential issues with efficacy and toxicity.
Target Audience
The primary audience includes researchers and scientists in drug discovery and development who need mechanistic insights into drug efficacy and toxicity to make informed decisions about progressing assets to clinical trials.
Features
- Simulates drug effects across various cell lines to predict potency and toxicity endpoints.
- Visualizes mechanisms of action by predicting genome-wide changes in gene expression and pathway activation.
- Identifies potential mechanism of action targets by analyzing perturbed pathways.
- Predicts growth inhibition and sensitivity in cancer cell lines, linking these to changes in apoptotic pathways.
- Characterizes the potential for hepatotoxicity by predicting drug-induced liver injury and results for 14 assay endpoints, including CYP450 inhibition and mitochondrial toxicity.
- Pathway Explorer tool to visualize predictions and generate testable hypotheses about drug perturbations.