From disease patterns to drug pipelines to healthcare infrastructure — BioInt turns life-sciences data into decision-grade intelligence. Built for researchers, strategists, and investors who need to see what's coming before it arrives.
BioInt ingests clinical trials, genomic databases, regulatory filings, and market data. It models disease dynamics, R&D success probabilities, and economic impacts — giving you a clear view of the biological and economic forces that shape health outcomes and market outcomes alike.
Incidence vs. model forecast — surveillance signal integration and early-warning capability. Compartmental dynamics (SIR/SEIR) with Bayesian parameter estimation.
Built for top-tier epidemiologists, computational biologists, and bioengineers. Stochastic ODE solvers, MCMC posterior sampling, particle filtering for state estimation. Integrates with WHO, CDC, ECDC surveillance feeds. Agent-based and metapopulation extensions. Real-time Rt and growth rate estimation.
Real-time epidemiological signals, outbreak patterns, pathogen genomics. Early-warning models for emerging threats and seasonal forecasting. Integrates WHO, CDC, ECDC, and regional surveillance networks. Compartmental models (SIR, SEIR) and agent-based simulations.
Drug development pipelines, clinical trial outcomes, regulatory milestones. Forecast approval probabilities and market entry timelines. Coverage of 12,000+ pipeline assets across therapeutic areas. Bayesian success-rate modeling.
Hospital capacity, supply chain resilience, workforce dynamics. Model cascading impacts of demand shocks and resource constraints. Used by public health agencies and hospital networks. Queueing and network-flow optimization.
Connect biomedical events to economic outcomes. GDP impact of pandemics, biotech valuation drivers, healthcare spending trajectories. Cited in policy and investment research. CGE and DSGE integration.
Attrition from discovery through approval — industry-standard funnel. Phase transition probabilities derived from Tufts CSDD and FDA approval databases.
Clinical, genomic, regulatory, and market data from 2,400+ validated sources.
Unified schemas, entity resolution, temporal alignment.
Statistical and ML models for forecasting and scenario analysis.
Dashboards, APIs, and reports for researchers and decision-makers.
Phase progression, enrollment, endpoints, regulatory submissions.
Variant surveillance, expression data, biomarker discovery signals.
FDA, EMA, global agency filings, approvals, safety signals.
Surveillance data, outbreak reports, incidence modeling inputs.
Pricing, reimbursement, healthcare spending, sector indices.
R&D portfolio optimization, competitive intelligence, market entry timing.
Epidemic preparedness, resource allocation, policy scenario modeling.
Biotech valuation, clinical trial catalysts, sector rotation signals.
Drug shortage prediction, manufacturing risk, logistics optimization.