Preclinical assessment of antigen-specific chimeric antigen receptor regulatory T cells for use in solid organ transplantation.

A primary goal in transplantation medicine is the induction of a tolerogenic environment for prevention of transplant rejection without the need for long-term pharmacological immunosuppression. Generation of alloantigen-specific regulatory T cells (Tregs) by transduction with chimeric antigen receptors (CARs) is a promising strategy to achieve this goal. This publication reports the preclinical characterization of Tregs (TR101) transduced with a human leukocyte antigen (HLA)-A*02 CAR lentiviral vector (TX200) designated to induce immunosuppression of allograft-specific effector T cells in HLA-A*02-negative recipients of HLA-A*02-positive transplants. In vitro results demonstrated specificity, immunosuppressive function, and safety of TX200-TR101. In NOD scid gamma (NSG) mice, TX200-TR101 prevented graft-versus-host disease (GvHD) in a xenogeneic GvHD model and TX200-TR101 Tregs localized to human HLA-A*02-positive skin transplants in a transplant model. TX200-TR101 persisted over the entire duration of a 3-month study in humanized HLA-A*02 NSG mice and remained stable, without switching to a proinflammatory phenotype. Concomitant tacrolimus did not impair TX200-TR101 Treg survival or their ability to inhibit peripheral blood mononuclear cell (PBMC) engraftment. These data demonstrate that TX200-TR101 is specific, stable, efficacious, and safe in preclinical models, and provide the basis for a first-in-human study.

Developing global regression models for metabolite concentration prediction regardless of cell line.

Following the Process Analytical Technology (PAT) of the Food and Drug Administration (FDA), drug manufacturers are encouraged to develop innovative techniques in order to monitor and understand their processes in a better way. Within this framework, it has been demonstrated that Raman spectroscopy coupled with chemometric tools allow to predict critical parameters of mammalian cell cultures in-line and in real time. However, the development of robust and predictive regression models clearly requires many batches in order to take into account inter-batch variability and enhance models accuracy. Nevertheless, this heavy procedure has to be repeated for every new line of cell culture involving many resources. This is why we propose in this paper to develop global regression models taking into account different cell lines. Such models are finally transferred to any culture of the cells involved. This article first demonstrates the feasibility of developing regression models, not only for mammalian cell lines (CHO and HeLa cell cultures), but also for insect cell lines (Sf9 cell cultures). Then global regression models are generated, based on CHO cells, HeLa cells, and Sf9 cells. Finally, these models are evaluated considering a fourth cell line(HEK cells). In addition to suitable predictions of glucose and lactate concentration of HEK cell cultures, we expose that by adding a single HEK-cell culture to the calibration set, the predictive ability of the regression models are substantially increased. In this way, we demonstrate that using global models, it is not necessary to consider many cultures of a new cell line in order to obtain accurate models. Biotechnol. Bioeng. 2017;114: 2550-2559. © 2017 Wiley Periodicals, Inc.