What quantitative solutions does API provide?

From preclinical research to clinical trials, our team of leading pharmacologists, biostatisticians, and bioinformaticians delivers comprehensive, data-driven solutions. We work closely with you to customize strategies that align with your goals, ensuring a streamlined development process that maximizes efficiency and impact. Whether it’s optimizing study designs, advancing pharmacokinetic analysis, or leveraging AI for biomarker selection, our services empower you to bring your innovation to market safely and effectively.

K&R 24 762

Quantitative Solutions Services

Preclinical ADME and Translational Pharmacology

Comprehensive support for preclinical and translational pharmacology, from PK analysis to biomarker selection.

  • Pharmacokinetics (PK) and Toxicokinetics (TK): Ensure precise first-in-human (FIH) and allometric scaling.
  • Safety Assessments: Evaluate No Observed Adverse Effect Level (NOAEL) and Minimum Anticipated Biological Effect Level (MABEL).
  • Bioinformatics and Biomarker Selection: Leverage multi-omic approaches for pharmacodynamic and disease-specific biomarkers.

Biostatistics Services

Expert biostatistical services covering study design, analysis, and data visualization.

  • Clinical and Preclinical Study Design: Tailored support for the unique needs of each life sciences client.
  • Statistical Analysis Plans: Power and sample size calculations, data summaries, adverse event analysis, and endpoint results presentations.
  • Shiny Apps Development: Customized tools for effective data visualization and analysis.
  • Data Review: Missing data imputation (LOCF) and error detection, including outliers and out-of-range values.
  • Statistical Programming: CDISC-compliant dataset programming, Analysis Data Model (ADaM) and Study Data Tabulation Model (SDTM) development, and generation of tables, listings, and figures (TLFs) for reports.
  • Dose-Finding and Dose-Response Analysis: Focused on Phase 1 clinical trials and other therapeutic evaluations.
  • Support for DSMB/DMC: Preparation of data outputs for Data Safety Monitoring Boards (DSMB) or Data Monitoring Committees (DMC).

Clinical Pharmacology: Phase 1 – 3

Understanding drug interactions is essential for developing safe and effective therapies. We leverage advanced pharmacokinetics, Bayesian modeling, and clinical trial simulations to optimize dosing and outcomes.

  • Clinical Study Design, Planning, Analysis, Reporting: Customized study designs that encompass first-in-human studies, bioavailability and bioequivalence evaluations, drug-drug interaction assessments, food effect studies, QT interval prolongation evaluations, organ impairment analysis, ethnic bridging strategies, radio-labelled mass balance for ADME, and pediatric pharmacokinetics/pharmacodynamics.
  • PK Analysis Plan: Rich sampling pharmacokinetics using non-compartmental and compartmental approaches, with PK-PD correlations (direct and indirect) using Phoenix WinNonlin™.
  • Population Pharmacokinetics (Sparse Sampling): Advanced modeling with NonMem.
  • Physiologically Based Modelling (PBPK): PBPK-PD analysis with Gastroplus™ and PKSim.
  • Therapeutic Window and Dose-Response: Clinical trial simulations for optimized dosing.
  • Disease State Modeling: Comprehensive modeling for various disease states to inform clinical strategies.
  • Gap Analysis & Clinical Pharmacology Plan: Idecntifying key areas for improvement to support robust clinical pharmacology plans.

Quantitative Systems & Translational Pharmacology (QSP & QTP)

Data-driven pharmacology modeling and mechanism of action insights to predict clinical outcomes.

  • Modeling and Systems Pharmacology: Use advanced network analysis and disease models to predict new molecule interactions and clinical outcomes.
  • Mechanism of Action in Humans: Detailed insights into drug mechanisms through systems and molecular pharmacology.
  • Quantitative Translational Pharmacology: Leverage data-driven strategies to translate findings from models to human applications, optimizing therapeutic impact.

Bioinformatics

Multi-omics and molecular data integration for target and biomarker selection, with advanced spatial and bulk analysis.

  • Multi-Omics: Expertise in genomics, transcriptomics, lipidomics, proteomics, and microbiome analysis.
  • Target and Biomarker Selection: Identify critical targets and biomarkers for therapeutic development.
  • Spatial and Bulk Data Analysis: Advanced spatial single-cell and spot-level RNA sequencing, alongside bulk data analysis.
  • Gene-Set and Molecular Network Analysis: Integrate gene expression profiles using complex molecular interaction networks for deeper insights.
  • Intratumor Heterogeneity: Quantify and visualize tumor diversity at the molecular level.

Artificial Intelligence

AI-driven machine learning solutions for biomarker selection, patient stratification, and clinical study design. Our customizable approach allows us to tailor solutions to your project’s specific needs.

  • Machine Learning & Artificial Intelligence Consultation: Problem statement and solutions.
  • Machine Learning & Deep Learning: Advanced algorithms for data analysis and predictions.
  • Biomarker and Patient Selection: Identify biomarker patterns and predict patient responders for personalized therapies.
  • PK/QSP Integration: AI can be applied independently or in conjunction with pharmacokinetic and quantitative systems pharmacology methods for enhanced decision-making.

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Meet Our Quantitative Solutions Team

Corrine Campanella Headshot
Scott Profile Picture 2024 Large
Marawan Ahmed
Erfan Ghasemi
Morteza Haji Hosseini
Fernanda Talrico
Nastaran Hajizadeh Bastani

Ready to take your life sciences innovation to the next level?

Contact us today for a free 1-hour discovery consultation to determine how we can bring your idea to market together.