Project Overview

SMART CAMP (Critical Analytics for Manufacturing Personalized-Medicine) is a new interdisciplinary research programme in Singapore (CREATE international research campus and innovation hub) and at the Massachusetts Institute of Technology (MIT). SMART CAMP addresses key technology bottlenecks in cell therapy manufacturing: (i) critical quality attributes of safe, effective cell therapy products; and (ii) integrated process analytics to monitor and modulate those attributes. While cell therapies are poised to transform healthcare for both the industry and the patient, there remain many outstanding scientific and technical challenges to significant global impact that this R&D programme addresses. This high-impact focus includes measurement and feedback control of processing parameters (process analytic technologies, or PAT) that contribute to cell viability and function during cell proliferation, and the measurement at intermediate and final steps of the cell product properties correlated with positive therapeutic outcomes (critical quality attributes, or CQA).

This interdisciplinary team comprises engineers, biologists, clinicians, manufacturing, and data analytics experts from multiple MIT academic units, and multiple Singapore-based universities, research centres of excellence, and hospitals who are experienced at translational demonstrations of technologies in safety-regulated industries such as cell therapies. As with all postdoctoral associates (PDAs) in SMART CAMP based in Singapore, the PDA will work in a diverse team of experts including several principal investigators (PIs) and PDAs, and receive direct mentorship regarding career development from a pair of who are based in Singapore and at MIT, respectively.

CAMP’s unique, enabling and cross-cutting capabilities include cell and clinical biology, microfluidics, real-time optics and spectroscopies, 3D-printed devices, process analytics, data analytics, and bioinformatics. This programme will demonstrate these approaches required of cell-based personalized medicine through three translational testbeds (three Flagship Projects), ultimately facilitating access for more patients to life-saving, approved cell therapies for currently intractable health challenges. These flagship projects will address allogeneic and autologous cell therapy products, including but not limited to cell sources including adult stem/progenitor cells and immune cells for treatment of specific cancers, tissue degeneration, and autoimmune diseases.

Flagship Project 1: Label-free critical quality attributes (CQA) for personalized efficacy of cell therapies, including multivariate analysis of biological and biophysical attributes

Flagship Project 2: Rapid critical quality attributes (CQA) for safety of cell sources & cell therapy products, including process analytic technologies (PAT)

Flagship Project 3: Integrated process analytic technologies (PAT) for cell proliferation and recovery, including in-line and intermittent monitoring to promote efficacy and safety CQA

Job Responsibilities

CAMP Flagship Project 3 – Computational modelling and process control automation

Process analytic technologies (PAT) for cell therapy manufacturing must be accessible to or integrated with the culture vessels in which the cells are expanded to sufficient cell number and quality. In closed systems, this requires process automation that will depend on computational modelling for efficient process adjustments that maintain basic culture conditions and targeted critical quality attributes (CQA) of the cells. To improve the quality of adult stem/progenitor cells and T cells grown for cell therapies, this PDA will build computational models that capture how environmental factors affect cell viability and function including specific CQA. The computational modelling will describe a dynamical system in which we use real-time data from the cell environment for predicting real-time cell potency and proliferation. When a prototype of a computational model is built, the PDA will then build feedback control systems, in concert with the computational modelling, in order to adjust environmental factors and optimize cell health during the growth process. Successful completion of this project will shed light on the biochemical determinants of cell function, thus enabling better control of cell manufacturing process.

This PDA position offers a rare opportunity for computational modelling to bridge the gap between theoretical discovery (for environmental influences affecting cell potency) and real-world implementation (for getting cells produced for human clinical trials). The PDA will work with an interdisciplinary team of engineers, biologists, and clinicians in CAMP developing an advanced manufacturing platform with real-time monitoring of cell growth, and endpoint measures of cell function, potency, and clinical efficacy.

• Computational modelling of a dynamical system using differential equations
• Model selection in addition to model fitting and parameter estimation
• Design control strategies for manipulating the chemical and physical environment of the cells to achieve desired biological outcomes
• Demonstrate candidate models with CAMP collaborators for at least one cell type and CQA set

Job Requirements

• Ph.D. in biological/biomedical engineering, chemical engineering, mechanical engineering, electrical engineering, quantitative biology, or a relevant field
• Computational modelling experience and experience with differential equations
• Fluent computer programming in a relevant language
• Creativity to solve challenging technical problems in the presence of biological and technical uncertainty
• Good communication skills to work with researchers from a variety of biological, clinical, and engineering backgrounds
• Good track record of publications and scientific output
• Willing to participate in international teleconferences conducted at early/late hours
• Self-motivated, independent, with superior organizational and analytical skills
• Able and committed to work in Singapore. Willing to commute and meet regularly with co-workers at NUS, Duke-NUS, Biopolis, etc.

Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.