PK/PD-driven virtual patient and clinical trial simulation toolkit. Generate copula-based virtual patients, run adaptive multi-arm trials, and produce tailored protocols ready for stakeholder review.
Refua Clinical is a simulation package for PK/PD-driven clinical trial design. It generates copula-based virtual patients, runs adaptive multi-arm trial simulations with Bayesian response-adaptive allocation, and produces a tailored protocol that can be re-simulated with modified inputs.
The package directly integrates with the core Refua toolkit, accepting ADMET profiles and affinity predictions as inputs to inform simulation parameters automatically.
Generate realistic virtual patient populations using Gaussian copulas with configurable marginals and covariate effects for each trial arm.
Score candidate designs on simulated operating characteristics and expected cost to recommend optimal sample sizes and interim cadences.
Explore the trade-off frontier between power, cost, and timeline with Pareto-front outputs for informed decision-making.
Run VOI scenarios to determine whether additional enrollment is worth the investment before committing to expansion decisions.
Assess covariate shift, overlap scores, and risk levels for extrapolating results from reference to target populations.
Generate narratives, interim decision-card summaries, and prioritized actionable recommendations for stakeholder review.
Initialize a trial config with init-config or accept ADMET inputs from Refua.
Run the PK/PD simulation with virtual patients, adaptive allocation, and early stopping rules.
Generate a tailored protocol recommendation with optimal sample size and interim schedule.
Run multi-objective optimization and VOI analysis to refine the design.
Generate explainable advice with narratives and prioritized recommendations.
Refua Clinical supports both small molecule and biologics modalities. Biologics mode adds IV/SC route support, interval dosing, and optional TMDD-like clearance scaling for antibody and protein therapeutics.
The ADMET-aware simulation path automatically adjusts PK parameters based on Refua ADMET profiles, creating a seamless bridge from molecular design to clinical trial planning.
pip install refua-clinicalWith ADMET integration:
pip install "refua-clinical[admet]"refua-clinical workup \
--config config.yaml \
--output-dir artifacts/full_workup \
--include-sensitivityfrom refua_clinical import ClinicalStudy
study = (
ClinicalStudy.default()
.trial(
trial_id="oncology-demo",
indication="Oncology",
phase="Phase II",
replicates=96,
)
.set("enrollment.total_n", 220)
)
run = study.simulate()
protocol = run.recommend_protocol(replicates_per_candidate=30)
print(run.summary["power"], protocol.protocol["protocol_id"])Refua Clinical brings modern simulation methods and regulatory-informed defaults to clinical trial design, helping teams make better decisions before the first patient is enrolled.