To be effective as a drug, a potent molecule must reach its target in the body in sufficient concentration, and stay there in a bioactive form long enough for the expected biologic events to occur. Drug development involves assessment of absorption, distribution, metabolism and excretion (ADME) increasingly earlier in the discovery process, at a stage when considered compounds are numerous but access to the physical samples is limited. In that context, computer models constitute valid alternatives to experiments. Here, we present the new SwissADME web tool that gives free access to a pool of fast yet robust predictive models for physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness, among which in-house proficient methods such as the BOILED-Egg, iLOGP and Bioavailability Radar. Easy efficient input and interpretation are ensured thanks to a user-friendly interface through the login-free website http://www.swissadme.ch. Specialists, but also nonexpert in cheminformatics or computational chemistry can predict rapidly key parameters for a collection of molecules to support their drug discovery endeavours.

Drug discovery aims to identify potential therapeutic compounds capable of modulating the activity of specific biological targets. Molecular docking can efficiently support this process by predicting binding interactions between small molecules and macromolecular targets and potentially accelerating screening campaigns. SwissDock is a computational tool released in 2011 as part of the SwissDrugDesign project, providing a free web-based service for small-molecule docking after automatized preparation of ligands and targets. Here, we present the latest version of SwissDock, in which EADock DSS has been replaced by two state-of-the-art docking programs, i.e. Attracting Cavities and AutoDock Vina. AutoDock Vina provides faster docking predictions, while Attracting Cavities offers more accurate results. Ligands can be imported in various ways, including as files, SMILES notation or molecular sketches. Targets can be imported as PDB files or identified by their PDB ID. In addition, advanced search options are available both for ligands and targets, giving users automatized access to widely-used databases. The web interface has been completely redesigned for interactive submission and analysis of docking results. Moreover, we developed a user-friendly command-line access which, in addition to all options of the web site, also enables covalent ligand docking with Attracting Cavities. The new version of SwissDock is freely available at https://www.swissdock.ch/.

Immune checkpoint inhibitors (ICIs) have revolutionised cancer therapy but frequently cause immune-related adverse events (irAEs). Description of late-onset and duration of irAEs in the literature is often incomplete. To investigate reporting and incidence of late-onset and long-lasting irAEs, we reviewed all registration trials leading to ICI's approval by the US FDA and/or EMA up to December 2019. We analysed real-world data from all lung cancer (LC) and melanoma (Mel) patients treated with approved ICIs at the University Hospital of Lausanne (CHUV) from 2011 to 2019. To account for the immortal time bias, we used a time-dependent analysis to assess the potential association between irAEs and overall survival (OS). Duration of irAEs and proportion of patients with ongoing toxicities at data cut-off were not specified in 56/62 (90%) publications of ICIs registration trials. In our real-world analysis, including 437 patients (217 LC, 220 Mel), 229 (52.4%) experienced at least one grade ≥2 toxicity, for a total of 318 reported irAEs, of which 112 (35.2%) were long-lasting (≥6 months) and about 40% were ongoing at a median follow-up of 369 days [194-695] or patient death. The cumulative probability of irAE onset from treatment initiation was 42.8%, 51.0% and 57.3% at 6, 12 and 24 months, respectively. The rate of ongoing toxicity from the time of first toxicity onset was 42.8%, 38.4% and 35.7% at 6, 12 and 24 months. Time-dependent analysis showed no significant association between the incidence of irAEs and OS in both cohorts (log Rank p = 0.67 and 0.19 for LC and Mel, respectively). Late-onset and long-lasting irAEs are underreported but common events during ICIs therapy. Time-dependent survival analysis is advocated to assess their impact on OS. Real-world evidence is warranted to fully capture and characterise late-onset and long-lasting irAEs in order to implement appropriate strategies for patient surveillance and follow-up.

Hit finding, scaffold hopping, and structure–activity relationship studies are important tasks in rational drug discovery. Implementation of these tasks strongly depends on the availability of compounds similar to a known bioactive molecule. SwissSimilarity is a web tool for low-to-high-throughput virtual screening of multiple chemical libraries to find molecules similar to a compound of interest. According to the similarity principle, the output list of molecules generated by SwissSimilarity is expected to be enriched in compounds that are likely to share common protein targets with the query molecule and that can, therefore, be acquired and tested experimentally in priority. Compound libraries available for screening using SwissSimilarity include approved drugs, clinical candidates, known bioactive molecules, commercially available and synthetically accessible compounds. The first version of SwissSimilarity launched in 2015 made use of various 2D and 3D molecular descriptors, including path-based FP2 fingerprints and ElectroShape vectors. However, during the last few years, new fingerprinting methods for molecular description have been developed or have become popular. Here we would like to announce the launch of the new version of the SwissSimilarity web tool, which features additional 2D and 3D methods for estimation of molecular similarity: extended-connectivity, MinHash, 2D pharmacophore, extended reduced graph, and extended 3D fingerprints. Moreover, it is now possible to screen for molecular structures having the same scaffold as the query compound. Additionally, all compound libraries available for screening in SwissSimilarity have been updated, and several new ones have been added to the list. Finally, the interface of the website has been comprehensively rebuilt to provide a better user experience. The new version of SwissSimilarity is freely available starting from December 2021.

PURPOSE: The first randomized trial of adjuvant treatment with checkpoint inhibitor in stage II melanoma reported a significant reduction in risk of tumor recurrence. This study evaluates two independent data sets to further document survival probabilities for patients with primary stage I and II melanoma. PATIENTS AND METHODS: The Central Malignant Melanoma Registry (CMMR) in Germany evaluated 17,544 patients with a primary diagnosis of stage I and II melanoma from 2000 to 2015. The exploratory cohort consisted of 6,725 patients from the Center for Dermato-Oncology at the University of Tübingen, and the confirmatory cohort consisted of 10,819 patients from 11 other German centers. Survival outcomes were compared with published American Joint Committee on Cancer version 8 (AJCCv8) stage I and II survival data. RESULTS: For the two CMMR cohorts in stage IA compared with the AJCCv8 cohort, melanoma-specific survival rates at 10 years were 95.1%-95.6% versus 98%; 89.7%-90.9% versus 94% in stage IB; 80.7%-83.1% versus 88% in stage IIA; 72.0%-79.9% versus 82% in stage IIB; and 57.6%-64.7% versus 75% in stage IIC, respectively. Recurrence rates were approximately twice as high as melanoma-specific mortality rates in stages IA-IIA. CONCLUSION: The melanoma-specific survival rates in the two CMMR cohorts across stages I and II are less favorable than published in AJCCv8. This has important implications for the consideration of adjuvant treatment in this population.