As of today, 20 disease modifying drugs (DMD) have been approved for the treatment of relapsing multiple sclerosis (MS) and, based on their efficacy, they can be grouped into moderate-efficacy DMDs and high-efficacy DMDs. The choice of the drug mostly relies on the judgement and experience of neurologists and the evaluation of therapeutic response can only be obtained by monitoring clinical and magnetic resonance imaging (MRI) status during follow up. In an era where therapies are focused on personalization, the aim of this study is to develop a modeling infrastructure to predict the evolution of relapsing MS and the response to treatments. We built a computational modeling infrastructure named UISS (Universal Immune System Simulator) able to simulate the main features and dynamics of the immune system activities. We extended UISS to simulate all the underlying MS pathogenesis and its interaction with the host immune system. This simulator is a multi-scale, multi-organ, agent based simulator with an attached module capable of simulating the dynamics of specific biological pathways at the molecular level. We simulated six MS patients with different relapsing-remitting courses. These patients were characterized on the basis of their age, sex, presence of oligoclonal bands, therapy and MRI lesion load at onset. The simulator framework is made freely available and can be used following the links provided in the availability section. Even though the model can be further personalized employing immunological parameters and genetic information, based on the available data we generated a few simulation scenarios for each patient, including those who matched the real clinical and MRI history. Moreover, for two patients, the simulator anticipated the timing of subsequent relapses, which really occurred, suggesting that UISS may have the potential to assist MS specialists in predicting the course of the disease and the response to treatment.

Background: This study assessed the nephrotoxicity of oral BRAF inhibitors (BRAFi), regorafenib (REG) and encorafenib (ENC), in metastatic colorectal cancer (mCRC), through an analysis of re-ports from the US Food and Drug Administration's Adverse Event Reporting System (FAERS) da-tabase. Methods: A descriptive and disproportional analyses were performed for all reports with ENC and REG as the primary suspect. Results: A total of 379 reports had at least one renal ADR, mainly related to REG (93.1%). Potential safety signals for REG particularly included chromaturia (n = 44; ROR = 12.00, CI 95% = 8.92-16.16; IC = 2.36, IC025-IC075 = 2.06-2.66), hydronephrosis (10; 8.70, 4.67-16.19; 1.85, 1.23-2.47), nephrotic syn-drome (7; 5.73, 2.73-12.03; 1.47, 0.73-2.21), renal impairment (53; 4.16, 3.17-5.45; 1.39, 1.12-1.66), dys-uria (19; 3.06, 1.95-4.81; 1.06, 0.61-1.52), renal failure (38; 1.66, 1.20-2.28; 0.49, 0.17-0.81), and acute kidney injury (AKI) (43; 1.46, 1.08-1.97; 0.37, 0.07-0.67). For ENC, consistent disproportionalities were observed for AKI (n = 11; ROR = 3.79, CI 95% = 2.09-6.90; IC = 1.32, IC025-IC075 = 0.72-1.91) and dysuria (4; 6.50, 2.43-17.39; 1.86, 0.88-2.85). Conclusions: These findings highlighted some not extensively reported renal ADRs that required further investigations to better characterize the safety profile of BRAFi in patients with mCRC.

Daridorexant, as the first Dual Orexin Receptor Antagonist (DORA) marketed in Europe, offers a novel therapeutic approach to insomnia. However, data regarding its real-world safety are scarce. Thus, the aim of this study was to assess its safety profile using a large-scale pharma-covigilance database. Daridorexant-related Adverse Drug Reaction (ADR) reports from the FDA Adverse Event Reporting System were scrutinized, and ADRs were selected using reporting odds ratio (ROR) as a measure of disproportionality. Frequencies of events related to daridorexant were compared to all other drugs (reference group, RG1) and only to other DORAs (RG2). Only significant disproportionalities to both RGs were evaluated in-depth. A total of 845 dari-dorexant-related reports were selected; nightmares (n = 146; Dari vs. RG1: ROR = 113.74; 95%CI[95.13, 136]; Dari vs. RG2: ROR = 2.35; 95CI%[1.93, 2.85]), depression (n = 22; Dari vs. RG1: 2.13; [1.39, 3.25]; Dari vs. RG2: ROR = 2.31; 95CI%[1.45, 3.67]), and hangover (n = 20; Dari vs. RG1: ROR = 127.92; 95CI%[81.98, 199.62]; Dari vs. RG2: 3.38; [2.04, 5.61]) were considered as safety signals. These data provide valuable insights into the real-world safety profile of dari-dorexant, supporting the existence of safety signals related to nightmares, depression, and hang-over.