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Using Model-based Meta-analysis to Improve Decision-making in Drug Development
Thu, November 03rd
オンデマンド・ウェビナー

Making the right choices in drug development often means the difference between getting a new medication to patients and it ending up in the scrap heap of failed programs. 承認された医薬品および開発中の医薬品の両方に関する公開情報は非常に多く存在します。こうした状況下で、スポンサー企業はどのように臨床試験データに基づいて、開発医薬品の成功への道筋をつける知見を獲得することができるでしょうか?

Model-based meta-analysis (MBMA) is an emerging methodology that quantifies clinical trial efficacy, tolerability, and safety information to enable strategic drug development decisions. The strategy involves a systematic search and tabulation of summary results from public sources which may be combined with proprietary clinical trial data. These data are then analyzed using nonlinear regression models which characterize the impacts of drug class, drug, dose, and time on the response(s) of interest.

In this webinar, Dr. Leon Bax will present several case studies that illustrate how MBMA was used to help sponsors:

  • Position a drug within the competitive landscape
  • Optimize clinical trial design
  • Inform portfolio and marketing decisions to ensure commercial success

About Our Speaker

Webinar-1speaker-BaxDr. Leon Bax is a director of consulting services at Certara Strategic Consulting. He has over 10 years of academic and consulting experience in epidemiological and statistical modeling, with a focus on methodology of mid and late phase drug development. He holds two PhDs, one in Clinical Epidemiology and one in Medical Informatics, and is an expert in the field of meta-analysis.

Dr. Bax has worked on projects in a wide range of therapeutic areas such as cardiovascular medicine, oncology, anesthesiology, gastroenterology, immunology, and sports medicine. He has supported filings for the FDA and EMA with model-based drug development strategies as well as with statistical and epidemiological analyses.

Dr. Bax is fluent in Dutch, English, and German. Having lived and worked in Japan for over 7 years, he is also able to communicate in Japanese at a business level and has a special interest in drug development in Japan and the Asia-Pacific region. When he is not behind his computer, he plays tennis and enjoys the outdoors with his wife.

Making the right choices in drug development often means the difference between getting a new medication to patients and it ending up in the scrap heap of failed programs. 承認された医薬品および開発中の医薬品の両方に関する公開情報は非常に多く存在します。こうした状況下で、スポンサー企業はどのように臨床試験データに基づいて、開発医薬品の成功への道筋をつける知見を獲得することができるでしょうか?

Model-based meta-analysis (MBMA) is an emerging methodology that quantifies clinical trial efficacy, tolerability, and safety information to enable strategic drug development decisions. The strategy involves a systematic search and tabulation of summary results from public sources which may be combined with proprietary clinical trial data. These data are then analyzed using nonlinear regression models which characterize the impacts of drug class, drug, dose, and time on the response(s) of interest.

In this webinar, Dr. Leon Bax presented several case studies that illustrate how MBMA was used to help sponsors:

  • Position a drug within the competitive landscape
  • Optimize clinical trial design
  • Inform portfolio and marketing decisions to ensure commercial success
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