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Simple Summary: Chemotherapy-induced neuropathy is a major clinical problem, with limited treatments available to try to reverse it. Some preliminary data suggested that palmitoylethanolamide (PEA) may effectively treat this condition. Pursuant to this, a placebo-controlled, double-blind, randomized phase 2 clinical trial was developed to look for evidence to support a future, more definitive phase 3 clinical trial. Eighty-nine patients participated in this clinical trial. Unfortunately, the data from the present phase 2 trial did not support the idea that PEA was useful in this situation. Background: Chemotherapy-induced peripheral neuropathy (CIPN) from oxaliplatin and taxane drugs is a bothersome toxicity. Palmitoylethanolamide (PEA) has been reported to improve myelinated nerve fiber function in patients experiencing painful CIPN. We conducted a double-blind, placebo-controlled, randomized trial of PEA in patients with established CIPN. Methods: Eligible patients were adults who had pain, numbness, tingling, or other symptoms of CIPN for at least three months following completion of paclitaxel, oxaliplatin, or cisplatin-based chemotherapy. Study patients were randomized to one of the two treatment groups (PEA versus placebo, both administered either once or twice daily). The CIPN20 questionnaire was assessed weekly. Results: A total of 17 males and 71 females participated in the study; most had neuropathy from paclitaxel. Most (85%) finished 8 weeks of treatment. There was no suggestion that either of the PEA arms did any better than the combined placebo arms. There was no signal of significant toxicity differences between the three study arms. Quality of life outcome measures were similar between the study arms, as were cognitive function evaluations. Discussion: PEA failed to improve established CIPN. Future trials might explore whether PEA may be effective in preventing CIPN or cognitive changes based on data that suggest it may be helpful in this situation. Conclusions: PEA failed to improve established chemotherapy-induced neuropathy. [ABSTRACT FROM AUTHOR]

Agent-based modeling has been used to characterize the nested control loops and non-linear dynamics associated with inflammatory and immune responses, particularly as a means of visualizing putative mechanistic hypotheses. This process is termed dynamic knowledge representation and serves a critical role in facilitating the ability to test and potentially falsify hypotheses in the current data- and hypothesis-rich biomedical research environment. Importantly, dynamic computational modeling aids in identifying useful abstractions, a fundamental scientific principle that pervades the physical sciences. Recognizing the critical scientific role of abstraction provides an intellectual and methodological counterweight to the tendency in biology to emphasize comprehensive description as the primary manifestation of biological knowledge. Transplant immunology represents yet another example of the challenge of identifying sufficient understanding of the inflammatory/immune response in order to develop and refine clinically effective interventions. Advances in immunosuppressive therapies have greatly improved solid organ transplant (SOT) outcomes, most notably by reducing and treating acute rejection. The end goal of these transplant immune strategies is to facilitate effective control of the balance between regulatory T cells and the effector/cytotoxic T-cell populations in order to generate, and ideally maintain, a tolerant phenotype. Characterizing the dynamics of immune cell populations and the interactive feedback loops that lead to graft rejection or tolerance is extremely challenging, but is necessary if rational modulation to induce transplant tolerance is to be accomplished. Herein is presented the solid organ agent-based model (SOTABM) as an initial example of an agent-based model (ABM) that abstractly reproduces the cellular and molecular components of the immune response to SOT. Despite its abstract nature, the SOTABM is able to qualitatively reproduce acute rejection and the suppression of acute rejection by immunosuppression to generate transplant tolerance. The SOTABM is intended as an initial example of how ABMs can be used to dynamically represent mechanistic knowledge concerning transplant immunology in a scalable and expandable form and can thus potentially serve as useful adjuncts to the investigation and development of control strategies to induce transplant tolerance. [ABSTRACT FROM AUTHOR]

The complex interactions that characterize acute wound healing have stymied the development of effective therapeutic modalities. The use of computational models holds the promise to improve our basic approach to understanding the process. By modifying an existing ordinary differential equation model of systemic inflammation to simulate local wound healing, we expect to improve the understanding of the underlying complexities of wound healing and thus allow for the development of novel, targeted therapeutic strategies. The modifications in this local acute wound healing model include: evolution from a systemic model to a local model, the incorporation of fibroblast activity, and the effects of tissue oxygenation. Using these modifications we are able to simulate impaired wound healing in hypoxic wounds with varying levels of contamination. Possible therapeutic targets, such as fibroblast death rate and rate of fibroblast recruitment, have been identified by computational analysis. This model is a step toward constructing an integrative systems biology model of human wound healing. [ABSTRACT FROM AUTHOR]