PK Analysis

Characterize and explore your drug’s kinetics for reports and insights into patient effects

  • What is the extent of exposure to our drug?
  • What is the impact of between-patient variability? How large is it?
  • Do we need to reformulate?
  • Is there a gender difference? Is exposure different in Asia/Africa/Europe?
  • Pre-clinical and clinical PK

qPharmetra can help!
  • From simple non-compartmental to complex non-linear mixed effects, population PK modeling, qPharmetra has the know-how to find these answers
  • Your Result: qPharmetra’s systematic approach, automation, quality processes, and standardized reporting give you robust, submission-ready results
PK/PD Analysis

Predict your dose-response for efficacy, tolerability and safety

  • What is our exposure-response?
  • What doses should we test?
  • Do we know the minimally effective dose?
  • How many adverse events are expected at higher doses?
  • How would a reformulation affect efficacy and tolerability?
  • How do different populations respond?
qPharmetra can find pragmatic answers to these questions
  • Quantifying the crucial yet uncertain relationships between increased exposure and efficacy or side effects is critical to your success.
  • PK/PD modeling concretely describes the performance characteristics of your drug
  • We take into account the mechanism of action, patient characteristics and the impacts of dose and time
  • Enable Dose selection, trial Design, partnering discussions, and regulatory Submissions
  • Your Result: Robust and Clear Predictions of Efficacy, Safety and Tolerability
Virtual Trials

Gauge your next trial’s probability of success and test alternative designs before you invest

  • What is the best design for the next trial?
  • Which patient populations will maximize the chance of success?
  • What is our probability of success against the standard of care?
  • Do we need a PoC trial?

qPharmetra has the Expertise and Computing Power to Solve these Problems
  • qPharmetra are experts at using Clinical Trial Simulation (CTS) to “war game” alternatives and hypothetical scenarios before investing in the next trial
  • We use simulation to turn models of your data into data-based recommendations
  • Your Result: Design trials that maximize the probability of trial and program success
Model-Based Meta-Analysis

Use publicly available data to model the competitive landscape; Locate your drug in a crowded market

  • Is this drug better than the standard of care?
  • Where will it fit in the competitive landscape?
  • What is the placebo response? What is the time-course of disease progression?
  • Which biomarkers predict clinical success?
  • How do different populations respond to each drug in this area?

qPharmetra Uses Model-Based Meta-Analysis to Position Products in Competitive Markets
  • Glean insight from public data (literature, regulatory, conference proceedings)
  • Leverage other companies’ public data to learn from previous experience about biomarkers and clinical endpoints
  • Your Result: Know where your drug falls relative to competitors before you invest in expensive trials
Clinical Utility Analysis

Link your scientific data to quantitative measures of net patient benefit to guide development

  • Can we beat the standard of care?
  • Which effects of the drug are most important?
  • Which of these drives value? Uncertainty?
  • Do we continue with this program?
  • What is the “best” dose given efficacy and safety trade-offs?
  • Do we need to reformulate to avoid adverse effects, and if so what is the best way?

We are Experts with the Techniques to Answer these Questions
  • Clinical Utility Analysis employs proven tools from the field of Decision Analysis to measure efficacy and safety trade-offs
  • qPharmetra has extensive experience in both the math and the process of assessing clinical utility
  • Your Result: Bring teams together to assess a new drug’s strengths and assess the importance of liabilities
Mechanistic Models

Use knowledge of underlying processes to extrapolate beyond observed conditions

  • How influential is the target vs. off-target pharmacology?
  • How long is the effect expected to persist after disappearance of measurable drug?
  • Are drug-target interactions sufficiently strong to influence physiology?
  • How will the mechanism of action translate to the clinical setting?
  • Does enough of the get to the site of action to have a clinical effect?

Mechanistic, physiologically based models help to answer these questions:
  • Incorporate known mechanistic complexity into the modeling process
  • Integrate the right amount of biological complexity to enable key decisions
  • Simplify complex mechanistic representations to identify influential steps
  • Identify critical thresholds for the difference between disease and health
  • Your Result: A clear understanding of how your drug interacts with the biological target and what the downstream consequences are


Decision Analysis

Leverage your data to estimate your program’s probability of success, financial ramifications and business case

  • What is the value of my next trial? Is it worth doing?
  • Do we continue with this program?
  • Should we in-/out-license?
  • Can we beat the standard of care?
  • What is our probability of success?

qPharmetra Extends the Impact of Pharmacometrics with the Field of Decision Analysis
  • Your development strategy should be systematically integrated with your data analysis
  • qPharmetra has unique experience combining Pharmacometrics with Decision Analysis
  • Your Result: Data-driven strategy and robust assessment of risk and reward