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: 新規化合物と同一のクラスに含まれる既存医薬品の用量反応曲線の特性は?
• Optimize trial design: What is the impact of trial design features (e.g., time, endpoints) on treatment effects? How can we optimize dosing to maximize safety and efficacy?
• Inform go/no go, portfolio, marketing decisions: クラス最高の医薬品として差別化できるか?

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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.

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CODEx(コーデックス 臨床試験成績データベース)

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.

資料ダウンロード
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, PhD Chief Innovation Officer

治療戦略や試験デザイン、医薬品開発の意思決定の最適化を目的としたモデリング&シミュレーション手法の応用研究に長年取り組んでいます。世界有数のモデルに基づくメタ解析のエキスパートとして広く知られています。様々な論文や書籍を執筆し、その学術的貢献に対して複数の表彰を受けています。

Zierhut
Matthew Zierhut Vice President, Integrated Drug Development

サターラでは、Matthew Zierhut 博士が、モデルに基づくメタ解析 (model-based meta-analysis:MBMA) により、 外部の集積された臨床試験データを開発の意思決定および商品化・規制戦略に統合することを推進しています。Matt は臨床開発チームと密接に連携し、最も重要な意思決定を行う際にMBMAが最適な効果を発揮するよう、活用しています。

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