Jonathan Jaeger

Founder of Jaeger Consulting & Statistical Scientist

I’m a statistician with more than 10 years of experience in academia and the pharmaceutical industry. I specialized myself in applying Bayesian and adaptive statistical designs & strategies.

Early in my career, while I was under a PhD program, I developed a Bayesian penalized smoothing approach for solving differential equations with application to pharmacokinetic and recovery studies (see Jaeger and Lambert 2013, 2014; Frasso, Jaeger, and Lambert 2016a, 2016b). In addition, during this period, I have provided statistical consulting services, helping researchers in applying appropriate statistical methodologies. I had also the opportunity to give statistical trainings for statisticians and non-statisticians.

I joined the food industry in 2014 where I have contributed, in a fully in-house model, to the clinical development and clinical operations in the area of preterm nutrition (Rigo et al. 2017) and other nutrition solutions (Binia et al. 2015).

In 2016, I moved to the pharmaceutical industry where I was lead statistician in support of phase I-III drug development in multiple therapeutic areas (haemato-oncology, oncology and infection) and novel therapeutic products (CAR T cells, checkpoint inhibitors, radiotherapeutics, antibody drug conjugates, …). Given the high unmet medical need context and novel therapy setting, rigorous and agile statistical expertise was essential to maneuver the clinical project seamlessly between clinical development needs, regulatory requirements and operational challenges.

I have created Jaeger Consulting in 2020 with the goal to nurture early and late clinical development with statistical innovation. Bayesian approaches, adaptive design strategies and informed quantitative decision-making tools are the basis elements promoted for impacting and fastering the clinical development.

Mid 2021, I have decided to support full time Tigen, a company aiming to bring effective cell therapies to cancer patients. Within Tigen, I had the chance to be responsible for creating, implementing and maintaining the strategic direction for data continuity & statistically driven quantitative-based decision making across technical operations, scientific and translational development, clinical research & development, and business development.

Since January 2023, I’m back to consulting, aiming even more to bring biometrics innovation and open-source solutions to support clinical development & operations. And always with one motto - Have fun & #FC!

References

Binia, Aristea, Jonathan Jaeger, Youyou Hu, Anurag Singh, and Diane Zimmermann. 2015. “Daily Potassium Intake and Sodium-to-Potassium Ratio in the Reduction of Blood Pressure: A Meta-Analysis of Randomized Controlled Trials.” Journal of Hypertension 33 (8): 1509–20. https://doi.org/10.1097/HJH.0000000000000611.

Frasso, Gianluca, Jonathan Jaeger, and Philippe Lambert. 2016a. “Inference in Dynamic Systems Using b-Splines and Quasilinearized ODE Penalties.” Biometrical Journal 58 (3): 691–714. https://doi.org/10.1002/bimj.201500082.

———. 2016b. “Parameter Estimation and Inference in Dynamic Systems Described by Linear Partial Differential Equations.” AStA Advances in Statistical Analysis 100 (3): 259–87. https://doi.org/10.1007/s10182-015-0257-5.

Jaeger, Jonathan, and Philippe Lambert. 2013. “Bayesian p-Spline Estimation in Hierarchical Models Specified by Systems of Affine Differential Equations.” Statistical Modelling 13: 3–40. https://doi.org/10.1177/1471082x12471371.

———. 2014. “Bayesian Penalized Smoothing Approaches in Models Specified Using Differential Equations with Unknown Error Distributions.” Journal of Applied Statistics 41 (12): 2709–26. https://doi.org/10.1080/02664763.2014.927839.

Rigo, Jacques, Jean-Michel Hascoët, Claude Billeaud, Jean-Charles Picaud, Fabio Mosca, Amandine Rubio, Elie Saliba, et al. 2017. “Growth and Nutritional Biomarkers of Preterm Infants Fed a New Powdered Human Milk Fortifier: A Randomized Trial.” Journal of Pediatric Gastroenterology and Nutrition 65 (4): e83. https://doi.org/10.1097/MPG.0000000000001686.