Gain insight into the safety and efficacy of your drug

Model-based meta analysis (MBMA) uses highly curated clinical trial data (Certara’s Clinical Trial Outcomes Databases) and pharmacology models to increase drug development productivity, quantitatively inform portfolio management and improve clinical trial success.


Certara’s MBMA approach offers three key advantages.

    • It supports bridging across studies, thereby enabling comparison of treatments and patient populations that may never have been tested together in the same clinical trial.
    • Our MBMA models are based on pharmacologic principles which facilitate incorporating wider spectrum data with regard to dose, observation time, and clinical trial designs
    • MBMA can be used to bring reality to synthetic patients and create synthetic control arms, offering advantages to typical synthetic control arms based on observational data.

Maximize your probability of success

Model-based meta analysis (MBMA) helps to answer important drug development questions including:
• Compare your drug vs the competition: What are the characteristics of the dose-response curves for existing drugs that are in the same class as a new compound?
• Optimize trial design: What is the impact of trial design features (e.g., time, endpoints) on treatment effects? 我们如何优化剂量以最大程度地提高安全性和效率?
• Inform go/no go, portfolio, marketing decisions: Can we differentiate the drug as best-in-class?

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Maximize your probability of success
Competitive landscaping with MBMA

Competitive landscaping with MBMA

There are very few active comparator trials in drug development. However, it is often important to assess a compound’s safety and efficacy profile in comparison to the standard of care and/or competitor drugs in development.

Model-based meta analysis (MBMA) enables indirect comparison, taking into account the impact of treatment, patient population, and trial characteristics on responses to medications.

This type of analysis, also called ‘competitive landscaping,’ helps us to understand potential differentiators in the drug profile and determine whether a drug is superior in the same drug class or across drug classes.


CODEx 和临床试验结果数据库

Certara’s model-based meta analysis (MBMA) projects use our Clinical Trial Outcomes Databases, which capture up-to-date information on trial design, patient characteristics, treatments, statistical analyses and safety and efficacy in more than 45 therapeutic areas.

We provide CODEx, an intuitive, interactive, web-based graphical interface, to unlock the value and richness of public and proprietary clinical outcome data. You can visualize, explore, analyze, and communicate the content of CODEx to a broad audience.

CODEx and Clinical Trial Outcomes Databases
More realistic synthetic control arms with MBMA

More realistic synthetic control arms with MBMA

MBMA-based synthetic control arms can more closely resemble the actual trial populations and trial conditions the treatments are evaluated in. Observational data can often be quite different from what is seen in a clinical trial.

Contact us for more information
Jaap 1@2x
Jaap Mandema,博士 首席创新官

Jaap 的主要经验在于应用建模和模拟来优化治疗策略、试验设计和药物开发决策。他是基于模型的荟萃分析方面的全球领先专家,发表了广泛的著作,并因其学术贡献获得了多个奖项。

Matthew Zierhut 副总裁,一体化药物开发

在 Certara,Matthew Zierhut 博士通过基于模型的元分析 (MBMA),推进将外部聚合临床试验数据整合到开发决策和商业和监管策略中。Matt 与临床开发团队密切合作,确保在做出最关键决策的时候,能利用 MBMA 发挥最佳影响力。

Bio Pic NancyZhang
Nancy Zhang, PhD Vice President, Integrated Drug Development, Database Products

Nancy develops and executes modeling and simulation strategies, as well as builds partnerships that foster growth and success for both parties. Her experience covers a broad range of therapeutic areas including oncology, diabetes, cardiovascular, anti-inflammatory and pain.


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