The use of bioinformatic data in autologous cell therapies

Abstract

Disclosed is a method for optimising an ex-vivo autologous cell culture procedure, said method including the steps of: obtaining and storing a patient's bioinformatic data; comparing said patient's bioinformatic data with known data in the form of bioinformatic data collected from other patients and / or other predetermined data such as genomic or proteomic data; and selecting ex-vivo cell culture procedure parameters based on the comparison between said patient's bioinformatic data and said known data. The selection can also be influenced by using the better data and / or culture parameter indicators determined by monitoring the outcome of plural cellular therapy attempts.

Description

technical field [0001] The present invention relates to the use of bioinformatics data associated with a patient to provide data related to autologous cell therapy techniques for the patient. Various uses of such data include optimizing in vitro (ex-vivo) cell culture systems; selecting the most appropriate treatment from a predetermined list of treatments; and feedback on patient outcomes to improve the accuracy of treatment techniques. Background technique [0002] Personalized cell therapy has recently shown remarkable promise. These therapies involve in principle taking a sample of cells from the patient, isolating cells of interest such as T cells or stem cells, optionally modifying such cells, proliferating the optionally modified cells, and administering the proliferated cells to the patient. Since the cells from each patient must be processed in isolation, conventional bulk production practices common to nearly every pharmaceutical manufacturing industry cannot be e...

AI Technical Summary

Problems solved by technology

Since cells from each patient must be processed in isolation, conventional bulk manufacturing practices common to nearly every pharmaceutical manufacturing industry cannot be employed in autologous therapies

Thus, while medical outcomes show significant promise, individualized protocols are costly due to lack of understanding to optimize unique batch production protocols, lack of clinical understanding to predict effects, e.g., potency of proliferating cells, and current lack of economies of scale Surprisingly Expensive, Commercialization of "Personalized" Cell Therapy Remains Considerable Challenges

[0003] The inventors have observed that inherently varying starting materials (quantity and quality of starting biological material) pose challenges in in vitro proliferation and automated production of cells and lead to concomitant effects on cell growth and prohibitive expenditure

While applicable to all cell sources and therapies, these challenges are particularly relevant to autologous therapies whereby each administered cell dose is unique to the recipient

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