Decision Analytics & Modeling

Leveraging best-in-class capabilities in modeling, simulation, mathematics, and Bayesian statistics, Certara employs advanced analytics frameworks and proprietary software to study and predict real world outcomes for drug value assessment.

Health Economics & Pricing

Real world evidence that quantifies value and potential of your product

Need to quantify the value and potential of your product? We’ve successfully conducted hundreds of pharmacoeconomic research projects across various disease areas for 20+ years:

One of our strengths is incorporating multiple pharmacoeconomic perspectives: US managed care organizations, EU payers’, and emerging market countries’ perspectives (BRIC, South Korea, Australia, and New Zealand).

Our simple but impactful framework supports developers’ preparation for HTA and payer appraisals. It systematically addresses the key questions explored by decision makers. Our clients follow this framework to inform early drug positioning as well as in preparing market access strategy.

Value-based pricing optimization

Industry executives require a transparent way of assessing and weighing risks of non-reimbursement while maximizing earnings to bolster negotiations towards garnering or maintaining therapy reimbursement. Our price models fulfill this need by guiding the choice of the optimal price/population/funding conditions for the given therapy, reducing uncertainty, and narrowing down the range of options to choose from.

Decades of experience in Pricing & Reimbursement Research you can count on:

  • Evaluate target product profiles from a P&R perspective and assess each against attributes and comparators for full insight into the influence on price and demand
  • Identify market specific cost-containment measures which may impact your product’s pricing and reimbursement status
  • Establish the price response and profit functions to identify the optimal price
  • Assess and validate your portfolio with respect to early stage planning and P&R implications
  • Understand prescribing decision-making based on behavioral responses (rather than preference judgment)
  • Determine price elasticity

Predictive Modeling & Simulations

From early stage development through lifecycle management—we help you navigate through the most difficult trade-offs

From early stage development through lifecycle management—we help you quantify and navigate the most difficult decisions. Our clients benefit from a global team of statisticians, epidemiologists and analysts with expertise in advanced predictive modeling and simulation.

Analytics and modeling services across the product lifecycle

Our team uses a variety of model types: Markov/cohort, decision analytic, Bayesian, patient-level simulation, discrete-event/Monte Carlo simulations, and typically include deterministic and probabilistic sensitivity analyses. What makes our work unique:

  • Thoughtful definition of the modeling framework and scope
  • Transparent and collaborative model building process
  • Advanced and broad modeling skills
  • Integrated solutions

Quantitative evidence synthesis

To ensure our work is of the highest quality, we employ all available and proven methods, e.g.:

  • Meta-analysis
  • Publication bias assessment
  • Heterogeneity assessment
  • Between groups homogeneity testing (categorical and continuous data)
  • Multivariate analyses
  • Estimation of overpopulation dispersion
  • Survival analysis including cross-over effect analysis
  • Generalized linear models (linear regression, logistic regression etc.) including prediction analysis
  • Network meta-analyses
  • Bayesian hierarchical models
  • Individual and trial level surrogate validation

Evidence Synthesis

Rigorous and transparent multi-source analyses to turn data and analytics into decision-making

Our multi-disciplinary teams offer a full range of Evidence Synthesis (literature review) capabilities to translate research into decision-making.

We match our literature review approach and data synthesis methods to the needs of your target audience.

Clinical Development Analytics

Superior analytics to evaluate the anticipated real-life benefit, risk and cost of new interventions and to support internal decisions

Certara offers superior analytics to evaluate and predict the real-life benefit, risk and cost of new interventions and to support internal decisions (market access strategy for products, portfolio prioritization, trial design), evidence building for a particular product and applications to authorities for approval and reimbursement. Here are some of the types of models we can develop for you:

Customized disease progression models. These models help our clients explore potential clinical scenarios, predict a future product’s value into an evolving therapeutic landscape, and identify uncertainties and gaps in evidence when there is still time to fill them.

Epidemiology forecasting models. These models consider the evolution of a disease and associated consequences to anticipate changes in therapy standards and populations for a particular disease and setting. Surrogates of clinically relevant endpoints are increasingly relied upon to assess benefit-risk and drive decisions on approval and reimbursement of new therapies.

Clinical program models. These models aid evaluating the probability of success for individual trials or clinical program under different scenarios. We strive to help decision-makers optimize their choice of target population, sample size, and choice of primary/secondary endpoints for optimal trial results. A few questions that our analytics have helped to answer:

Therapy sequence models. These models make it easy to assess increasingly complex therapeutic environments with multiple possible treatment sequences

Bridging to Effectiveness Studies

Our powerful study concept combining advanced predictive modeling with targeted clinical and real-life data analyse

Real-world clinical studies require enormous time and resources. They cannot be conducted in every country for every drug at all stages of drug lifecycles. Yet clinical development data and many real-world data sources may still inform the expected or relative effectiveness.

We minimize the uncertainties between clinical trial efficacy and real world effectiveness so that our clients can succeed with outcomes predictions and payer engagements.

Bridging studies combine advanced predictive and integrative modeling with targeted clinical and real-life data analyses. Such studies can be used to bridge from efficacy to effectiveness, from country to country, and from one population to another.

“The interaction of risk factors with drug efficacy is not what varies from one population to another—it is the distribution of these factors that does. This is why drug effectiveness may be different from country to country, or from one healthcare system to another.”

—Prof. Lucien Abenhaim, Pioneer of Pharmacoepidemiology, Former Executive Board Member, World Health Organization

We’ve also successfully employed these models to support risk-sharing agreements and value-based pricing.

Certara has pioneered a powerful approach to anticipate a product’s real-world value

The Health Outcomes Performance Estimator

We built the industry’s first dynamic and versatile tool to predict real world health outcomes

Building on over a decade of advanced modeling experience, we developed HOPE (the Health Outcomes Performance Estimator): the industry’s first tool dedicated to building predictive models for real world effectiveness.

HOPE translates clinical trial findings and population health knowledge into expected real world impact. It considers dynamic exposure and the influence of risk factors in its predictions.

HOPE is based on Certara’s epidemiological framework factoring in all known and potential drivers of effectiveness. It models complex interactions of disease characteristics, population risk factors, and dynamic medication use patterns with the efficacy of the molecule.

HOPE delivers robust results at an unmatched speed

  • Joint Simulation – Synthesize exposure, effectiveness drivers and outcomes from clinical trials and observational data sources
  • Rapid predictions – Estimate your real-world outcomes for any number of simulations
  • Visualization over time – Understand how exposure dynamics and other drivers of effectiveness influence outcomes in any user-defined virtual cohort
  • Strategic adaptability – Effortlessly compare a range of scenarios once a situation is specified

Decision Analytics for Outcomes-Based Contracting

Payers and reimbursement authorities are urging the adoption of performance-based contracting. What if you could identify the sources and quantify the impact of uncertainty around outcomes-based agreements?

The proprietary HOPE technology enables us to:

  • Test complex scenarios to optimize your plan design and inform payer negotiations and contracting
  • Understand what outcome, comparator and time horizon to select
  • Define the best methods to measure performance and opt for the most appropriate payment models

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