Terence Achuo Tem

1. Provide statistical expertise to CMC drug development and manufacturing activities:

• Perform statistical analyses using statistical methods for CMC applications e.g ANOVA, ANCOVA, equivalence tests, linear regression and mixed models, variance components analysis, Bayesian models, use of Confidence, Prediction and Tolerance intervals, etc in the following areas: Process design, process qualification, monitoring and continuous process verification, specifications settings, stability and comparability studies, analytical method development and validation.

• Deliver and communicate results in a customer-focused meaningful way to internal and external clients.

• Ensure that suitable statistical techniques are applied according to guidelines and requirements.

• Support regulatory submissions and investigations.

2. Develop and deliver statistics training courses to CMC audiences

• Create training material to support statistical training

• Organize and facilitate required trainings to ensure that statistical techniques are understood and applied correctly by the scientists.

• Promote constant feedback from scientists about needs on statistical computing and data management needs.

3. Change Management and Communication:

• Adapt, devise and implement novel data-analytical approaches and tools when they add value and insight.

• Keep updated on new CMC statistical developments within the academia, industry and the regulatory authorities.

• Provide statistical consulting to biotech and biopharma industries in various areas of drug development and manufacturing.

• Contribute to the design, modeling, statistical analysis, and process simulation using frequentist and Bayesian approaches.

• Provides non-clinical statistical support in immunogenicity assay development and validation by establishing Anti-drug antibody (ADA) cut points.

• Statistics in early drug development (non-clinical and pre-clinical projects): bioassay optimization and quality control, sample size estimation for in-vivo experiments, design of in-vitro/ex-vitro experiments, method comparison, method transfer.

• Promote and implement Quality by Design thinking and Design Space methodology. Apply DoE approaches for method and process development.

• Develop shiny applications for data visualization, analysis and quality control of bioassays for analytical laboratories.

• Communication with clients about statistical analysis opportunities.

• Good Clinical and Non-clinical practices (ICH, USP, JP Guidelines).