Computational blind challenges offer critical, unbiased opportunities to assess and accelerate scientific progress, as demonstrated by a breadth of breakthroughs over the past decade. We report the outcomes and key insights from an open science community blind challenge focused on computational methods in drug discovery, using lead optimization data from the AI-driven Structure-enabled Antiviral Platform Discovery Consortium's pan-coronavirus antiviral discovery program, in partnership with Polaris and the OpenADMET project. This collaborative initiative invited global participants from both academia and industry to develop and apply computational methods to predict the biochemical potency and crystallographic ligand poses of small molecules against key coronavirus targets, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV) main protease (Mpro), as well as multiple ADMET assay end points, using previously undisclosed comprehensive experimental drug discovery data sets as benchmarks. By evaluating submissions across multiple tasks and compounds, we established performance leaderboards and conducted meta-analyses to assess methodological strengths, common pitfalls, and areas for improvement. This analysis provides a foundation for best practices in real-world machine learning evaluation, grounded in community-driven benchmarking. We also highlight how next-generation platforms, such as Polaris, enable rigorous challenge design, embedded evaluation frameworks, and broad community engagement. This paper reports the collective findings of the challenge, offering a high-level overview of the data, evaluation infrastructure, and top-performing strategies. We further provide context and support for the accompanying papers authored by the challenge participants in this special issue, which explore individual approaches in greater depth. Together, these contributions aim to advance reproducible, trustworthy, and high-impact computational methods in drug discovery, and to explore best practices and pitfalls in future blind challenge design and execution, including planned initiatives for the OpenADMET project.
The integration of Industrialized Building Systems (IBS) and Building Information Modelling (BIM) represents a pivotal advancement in transforming conventional construction practices towards industrialization. Despite the increasing promotion of IBS under Malaysia’s Construction Industry Transformation Programme (CITP 2016–2020), its implementation continues to face challenges arising from fragmented project delivery methods, limited coordination, and poor planning. Concurrently, BIM offers significant capabilities to address these issues through digital collaboration, real-time information management, and design visualization. This paper explores the development of an IBS–BIM integrated framework aimed at enhancing productivity, efficiency, and sustainability in the Malaysian construction industry. A comprehensive literature review was conducted to identify the impacts of IBS–BIM integration, followed by a quantitative survey using structured questionnaires among key industry stakeholders—including architects, engineers, quantity surveyors, and project managers—supplemented by qualitative validation through expert focus group discussions. The findings reveal that the synergy between IBS and BIM mitigates major industry barriers, such as coordination gaps, rework, and design inconsistencies, while fostering collaboration, accuracy, and cost efficiency across project stages.
TPS3172 Background: KRAS is one of the most mutated driver oncogenes across solid tumors, and KRAS G12D missense mutations have high prevalence in pancreatic, colorectal (CRC), and endometrial cancers. QTX3034 is a highly-selective, non-covalent, orally bioavailable, multi-KRAS inhibitor with potent activity across several KRAS variants, particularly G12D. QTX3034 binds to GDP-bound forms of mutant and wild-type KRAS with (sub)nanomolar affinities, allosterically inhibiting its conversion to the active state. QTX3034 inhibits KRAS signaling in in vitro studies and displays synergy with EGFR inhibitors. In vivo evaluation of QTX3034 resulted in significant tumor growth inhibition across various tumor models, with tumor regressions observed in 100% of animals in both HPAC pancreatic and GP2D colorectal KRAS G12D xenograft models. QTX3034 exhibits brain penetration in preclinical studies, including an orthotopic model of intracranial efficacy. This clinical trial is now enrolling patients with advanced solid tumors harboring a KRASG12D mutation. Methods: This is a first-in-human, multicenter, open-label phase 1 study in adult patients with advanced solid tumors with KRASG12D mutations, without prior direct KRAS inhibitor treatment (NCT06227377). The primary objectives are to evaluate the safety and tolerability and to determine maximum tolerated dose (MTD) and/or recommended phase 2 dose (RP2D) of QTX3034 alone, and in combination with cetuximab. Secondary objectives are characterization of the PK profile and preliminary antitumor activity. Part 1 consists of two dose-escalation arms: QTX3034 monotherapy (advanced solid tumors) and QTX3034 plus cetuximab (CRC) and will enroll 3-4 subjects per cohort in a Bayesian Logistic Regression Model (BLRM) design. QTX3034 will be administered orally in 21-day cycles until disease progression, intolerable toxicity, or withdrawal from treatment. Exploratory paired biopsies will be collected in Cycle 2 in a group of patients in the dose-escalation phase. Serial ctDNA will be collected in all patients. Following identification of a RP2D, QTX3034 will be evaluated in dose-expansion cohorts of up to 30 patients with various KRASG12D mutated tumor types to determine preliminary activity: pancreatic cancer, CRC, non-small cell lung cancer and endometrial cancer. To further optimize the recommended dose, patients will be randomized between two dose levels in the pancreatic cancer cohort. QTX3034 plus cetuximab will be explored following identification of a recommended combination dose in patients with CRC. Clinical trial information: NCT06227377 .
Two codes developed to assist in safety assessments and nuclear emergency response planning are described and demonstrated. The atmospheric dispersion code PEARL uses an established consequence matrix developed using a unit source term methodology for a given set of atmospheric and release conditions. Solutions for specific source terms are established by multiplying this matrix by vectors of modifying factors characterizing the particular source term and dispersion parameters. This approach has a number of advantages, such as the ability to model time-dependent release characteristics of heat content and isotopic composition as well as the simultaneous evaluation of source terms over the full series of weather patterns in a single run; capabilities not previously available: Using site specific weather information, results can be structured in a number of different deterministic and probabilistic formats, permitting the direct identification of higher risk areas. Output generated by PEARL is used by the complementary computer code NERP to evaluate the effectiveness of specific countermeasures. By calculating the pathway doses and dose rates as a function of downwind distance and elapsed time from the start of release, NERP can represent any conceivable response scheme comprised of distance and time-dependent application and relaxation times for mitigating actions. The doses avoided by the response scheme can be readily determined for easy comparison against measures of effectiveness. Both codes employ menu-driven user interfaces to facilitate code use and run on a 486DX under MS-DOS.
L’articolo si propone di analizzare la produzione in lingua sarda di Antonella Anedda. A partire dalla raccolta Dal balcone del corpo si mettono in evidenza i principali snodi tematici connessi a questa particolare zona creativa della poesia aneddiana, relazionandoli con quelli maggiori presenti anche negli altri libri della poetessa. A conclusione del discorso si propone una interpretazione che indaga i motivi e le implicazioni intertestuali comportate dalla scelta del dialetto sardo, inteso dall’autrice come una lingua “ibrida” che di necessità si relaziona con il proprio vissuto esistenziale. The article aims to analyze Antonella Anedda's poems in Sardinian language. Starting from the collection Dal balcone del corpo, the article point out the major themes inside Anedda’s works and investigates reasons and intertextual implications involved in the choice of the Sardinian dialect, understood by the author as a "hybrid" language that necessarily relates to one's own existential experience.
