Crossing the chasm with pharmacometrics

Successful drug development and commercialization requires getting critical development and regulatory decisions right.

  • What is the exposure-response relationship for the drug?
  • What is the optimal dosing strategy?
  • Which patients would derive greatest benefit from this drug?

ファーマコメトリクスは数学および統計モデルを用いて、医薬品、疾患、試験情報を定量化し、これらの意思決定を支援します。The data used to build pharmacometric models comes from both internal preclinical and clinical data as well as external data on competitor drugs in the same class.

Pharmacometrics increases our understanding of factors that drive pharmacokinetic (PK) and pharmacodynamic (PD) variability. A well-designed pharmacometric strategy can also integrate knowledge across a drug’s preclinical and clinical development to support a “learn and confirm” paradigm.

We partner closely with clients, forming one cohesive and integrated team. ここで、お客様からの言葉をご紹介させてください。

“What I like most about Certara is not only their expertise, but also their commitment to their client.” – Clinical PK Manager at pharmaceutical company based in Switzerland

“What stands out about Certara is their timely responses and open dialogue.” – Translational Scientific Manager at mRNA therapeutics biotech

Optimize go/no-go decisions

Certara provides high-quality, regulatory-compliant pharmacokinetic and pharmacodynamic (PK/PD) analyses and modeling for regulatory submission packages.

Our pharmacometricians support:

  • Pre-clinical and clinical study analysis for new drug approvals
  • Line extensions
  • In-licensing options
  • Product portfolio decisions

With the largest global team of PhD, PharmD and MD consultants, we leverage quantitative methods to build a comprehensive knowledge-base of drug discovery, pre-clinical, early-phase clinical, literature, and competitor data, which can be used to optimize decisions, including the “go/no go” that will lead to commercial activities.


Optimize go/no-go decisions
Benefits of quantitative approaches

Benefits of quantitative approaches

90%+ of all novel drugs approved by the US FDA over the past few years have used pharmacometrics in their development program, with most leveraging Certara’s services or technology.

  • Make data-driven decisions at all stages of drug development through a quantitative framework
  • Design safer, targeted, and more efficient trials
  • Select the right dose for the right patients, the first time
  • Maximize the probability of commercial success
Read model informed drug development blog

モデリング & シミュレーションの成功はデータの質に依存します

解析プロジェクトに向けて最高品質のデータセットを必要としていませんか?Certara’s data programmers are experts in using SAS to code pharmacokinetic and pharmacodynamic (PK/PD) datasets.

  • Our data programmers create datasets for our projects
  • We create higher quality datasets that require fewer quality control cycles.
  • We can decrease the time between database lock and performing noncompartmental analysis (NCA), exploratory analysis, or PK/PD modeling
Learn more about PK/PD programming support
Modeling is only as good as your data
Bio Pic MarkLovern
Mark R. Lovern, PhD Sr. Vice President, Integrated Drug Development

Mark has over 15 years of experience applying modeling and simulation toward optimally informing drug development decision-making. Mark’s work history has been split between pharmaceutical companies such as GSK and UCB, and companies that support the biopharmaceutical industry. He has also taught over 50 technical training workshops on modeling tools and methodology. His most recent therapeutic area experience has been with infectious disease and autoimmune disorders.

Bio Pic JFMarier
JF Marier, PhD Sr. Vice President, Integrated Drug Development

JF has 25 years of experience performing PK, PK/PD and exposure-response analyses to support dosing rationale in various therapeutic areas. Specialties include oncology, rare diseases and pediatric populations. Over the last decade, he has provided pharmacometric analyses and strategic decisions that supported the regulatory approval of more than 25 small and large molecules.

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