Hybrid modeling of an ultracentrifugation process for separation of full and empty adeno-associated virus particles.

Ultracentrifugation is an attractive method for separating full and empty capsids, exploiting their density difference. Changes of the serotype/capsid, density of loading material, or the genetic information contained in the adeno-associated viruses (AAVs) require the adaptation of the harvesting parameters and the density gradient loaded onto the centrifuge. To streamline these adaptations, a mathematical model could support the design and testing of operating conditions.Here, hybrid models, which combine empirical functions with artificial neural networks, are proposed to describe the separation of full and empty capsids as a function of material and operational parameters, i.e., the harvest model. In addition, critical quality attributes are estimated by a quality model which is operating on top of the harvest model. The performance of these models was evaluated using test data and two additional blind runs. Also, a "what-if" analysis was conducted to investigate whether the models' predictions align with expectations.It is concluded that the models are sufficiently accurate to support the design of operating conditions, though the accuracy and applicability of the models can further be increased by training them on more specific data with higher variability.

Radiotherapy in Combination With Cytokine Treatment.

Radiotherapy (RT) plays an important role in the management of cancer patients. RT is used in more than 50% of patients during the course of their disease in a curative or palliative setting. In the past decades it became apparent that the abscopal effect induced by RT might be dependent on the activation of immune system, and that the induction of immunogenic cancer cell death and production of danger-associated molecular patterns from dying cells play a major role in the radiotherapy-mediated anti-tumor efficacy. Therefore, the combination of RT and immunotherapy is of a particular interest that is reflected in designing clinical trials to treat patients with various malignancies. The use of cytokines as immunoadjuvants in combination with RT has been explored over the last decades as one of the immunotherapeutic combinations to enhance the clinical response to anti-cancer treatment. Here we review mainly the data on the efficacy of IFN-α, IL-2, IL-2-based immunocytokines, GM-CSF, and TNF-α used in combinations with various radiotherapeutic techniques in clinical trials. Moreover, we discuss the potential of IL-15 and its analogs and IL-12 cytokines in combination with RT based on the efficacy in preclinical mouse tumor models.