Modeling approaches to inform every development decision.
Find in one place the key solutions offered by PhinC to support your development programs: from mechanistic understanding to clinical trial simulation, including PK/PD analysis, cardiac safety, non-compartmental pharmacokinetics, and advanced systems approaches.
PBPK
Anticipate the behavior of your drug candidate through a mechanistic approach that integrates physiology, compound properties, and experimental data to support and de-risk preclinical and clinical decisions.
- ADME prediction
- First-in-human
- DDI & food effect
- Special populations
QSP
Explore the biological complexity of your mechanisms of action with systems models capable of linking biology, pharmacology, and therapeutic hypotheses to guide your development strategy.
- Mechanistic modeling
- Systems perspective
- Hypothesis exploration
- Translational support
PK NCA - CDISC
Strengthen the reliability of your non-compartmental pharmacokinetic analyses and structure your data according to expected standards to improve the quality, traceability, and compliance of your deliverables.
- NCA analysis
- CDISC standards
- Quality & compliance
- Submission-ready deliverables
Pop PK / PD
Quantify variability, characterize exposure–response relationships, and identify dose optimization levers to build a development strategy that is more robust, clearer, and better substantiated.
- Exposure–response analysis
- Inter-individual variability
- Dose optimization
- Clinical decision support
QT / QTc
Evaluate the proarrhythmic risk of your compounds using a quantitative approach dedicated to cardiac safety, supporting development decisions and regulatory interactions with robust and actionable analyses.
- Cardiac safety
- Concentration–QTc analysis
- Regulatory Support
- Integrated interpretation
Clinical Trial Simulation (CTS)
Simulate different clinical trial scenarios to test your hypotheses, compare study designs, reduce uncertainty, and select the most relevant options before committing critical resources.
- Trial design comparison
- In silico scenarios
- Decision support
- Data Analysis and Interpretation