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Results for “multimodal modeling”

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PubMed2005

[A prospective multicenter clinical trial of breast conserving therapy for early breast cancer in China].

OBJECTIVE: To demonstrate the feasibility of breast conserving therapy (BCT) and establish a multimodality BCT model for early breast cancer in China. METHODS: A prospective multicenter case control study consisting of 4461 patients was carried out by the Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and nine other hospitals across China from November, 2001 to November, 2004, the result of BCT and mastectomy on early stage breast cancer were compared. Patients entry-primary tumor < or = 3 cm, primary tumor in periphery quadrant, pathology showed infiltrating carcinoma and clinical absence of locoregional lymphatic or distant metastasis. Patients rejection-multiple center cancer or diffused malignant calcified spots, previous radical radiation therapy in the chest, accompanying collogenolytic vascular granuloma and simultaneous pregnancy. RESULTS: Of these 4461 patients, breast conserving surgery was performed in 872 (19.5%) patients who were eligible for BCT, accounting for 9.0% of all operated breast cancer patients during the same period. The rates of local recurrence, metastasis and death were 1.0% (9/872), 1.3% (11/872) and 0.1% (1/872) in BCT group, versus 0.5% (18/3589), 1.4% (49/3589) and 0.1% (4/3589) in the mastectomy group. No statistical significant difference was found between these two groups (P > 0.05). Cosmetic evaluation of breast in BCT group was carried out postoperatively at points of six months, one year and two years with 89.7%, 91.1% and 86.6% of the patients assessed as excellent or fine cosmetic state respectively. CONCLUSION: Breast conserving therapy for early stage breast cancer is feasible in China, with no ominous effect on the survival and recurrence rate. Breast conserving therapy is able to improve not only the quality of life but also enhance the confidence of the patients, in addition to quasi-perfect cosmetic results. Standard comprehensive BCT involving multi-centers all concentrating on combination treatment should be widely adopted in China in the future. However, breast conserving surgery should selectively be used only for early stage breast cancer, and should be combined with postoperative radiotherapy, chemotherapy and hormone therapy in order to guarantee success.

Adult↗

PubMedDate not supplied

Preparing children and families for surgery: Mount Sinai's multidisciplinary perspective.

Upon learning that they must undergo surgery, children experience a range of emotions including fear, anger, guilt, and sadness. It has been demonstrated that children who are prepared for surgery and who have support throughout their hospitalization recover more quickly and have fewer emotional problems, such as separation anxiety and sleep disturbances, than those who are not prepared. Pre-surgical preparation programs allow children and their families the opportunity to preview the hospital experience in a supportive environment to reduce anxiety, increase knowledge, and enhance coping. Meet Me at Mount Sinai (MMAMS) is an innovative preoperative preparation program for children and their families that seeks to provide comprehensive emotional and cognitive preparation for surgery. MMAMS is led by a multi-disciplinary team of health care providers including a pediatric surgery nurse practitioner, a registered nurse, a social worker, and a child life specialist. The program utilizes a culturally-sensitive, multimodality preparation model to prepare children and families for the surgical experience.

Adaptation, Psychological↗

PubMed2006

Multimodality: a basis for augmentative and alternative communication--psycholinguistic, cognitive, and clinical/educational aspects.

PURPOSE: Message generating is a complex process involving a number of processes, including the selection of modes to use. When expressing a message, human communicators typically use a combination of modes. This phenomenon is often termed multimodality. This article explores the use of models that explain multimodality as an explanatory framework for augmentative and alternative communication (AAC). METHOD: Multimodality is analysed from a communication, psycholinguistic, and cognitive perspective. RESULTS: Theoretical and applied topics within AAC can be explained or described within the multimodality framework considering iconicity, simultaneous communication, lexical organization, and compatibility of communication modes. CONCLUSION: Consideration of multimodality is critical to understanding underlying processes in individuals who use AAC and individuals who interact with them.

Adult↗

PubMedDate not supplied

Multimode ligand binding in receptor site modeling: implementation in CoMFA.

Receptor site modeling methods usually use one binding mode (conformation and/or orientation) for each ligand in a 1:1 complex with receptor. Multiple modes should be considered instead because (1). they have frequently been observed experimentally; (2). in a series, ligands can bind in single yet different modes; and (3). a series may only exhibit one but unknown mode and a few plausible modes must be examined. For multimode binding, the observed ligand/receptor association constant is the sum of the association constants that characterize individual binding modes. This relation, when applied to Comparative Molecular Field Analysis (CoMFA), results in a dependence of the observed binding energy on the probe energies that is nonlinear in optimized parameters. The dependence was linearized to allow parameter optimization by the partial least-squares method that was used iteratively until self-consistency. In addition to the standard CoMFA output, the procedure objectively selects one or a few optimal binding modes out of a dozen or more modes that are considered for each ligand. The approach was applied to published data for binding of 34 polychlorinated dibenzofurans to the aryl hydrocarbon receptor. Descriptive and predictive abilities of the 16-mode model were significantly better than for the one-, two-, and four-mode models. Predominantly, edge-aligned modes were selected that are seldom used in CoMFA. Since inclusion of multimode binding only changes the form of the correlation equation and does not affect the number of optimized parameters, the improvement is believed to be due to a more realistic description.

Algorithms↗

PubMed2005

Aspects of the unity of consciousness and everyday memory failures.

We argue that analyzing everyday memory failures in terms of the "unity of consciousness" can elucidate the bases of such failures. A perfect unity amongst one's mental states is rare. In extreme cases the unity of consciousness can breakdown in dramatic fashion (e.g., in Dissociative Identity Disorder), but such breakdowns also occur in less dramatic ways that affect us in everyday life. For example, disruptions in the unity of consciousness can result in everyday memory failures, such as forgetting to put on a tie for an important formal meeting. After providing some philosophical background into the notions of "unity of consciousness" and "functionalism," we offer preliminary analyses of three examples of everyday memory failure. We then introduce and develop what we call the "unity model" of memory failure and show how it explains the examples. We also describe different ways that unity can break down which, in turn, can lead to memory failure and inappropriate behavior. We then show how slips of action and other kinds of cognitive failures (e.g., memory blocks) differ from everyday memory failures. Finally, we examine alternative models (e.g., Absentmindedness and Multimodal) arguing that the unity model is preferable, and then show how our model is consistent with some experimental results.

Cognition↗

PubMed2006

Description of depolarization effects in double-quantum solid state nuclear magnetic resonance experiments using multipole-multimode Floquet theory.

Using an analytical model based on multipole-multimode Floquet theory (MMFT), we describe the polarization loss (or depolarization) observed in double-quantum (DQ) dipolar recoupling magic angle spinning (MAS) experiments. Specifically, the factors responsible for depolarization are analyzed in terms of higher order corrections to the spin Hamiltonian in addition to the usual phenomenological decay rate constant. From the MMFT model and the effective Hamiltonians, we elucidate the rationale behind the inclusion of a phenomenological damping term in DQ recoupling experiments. As a test of this theoretical approach, the recoupling efficiency of one class of (13)C-(13)C and (13)C-(15)N resonance width dipolar recoupling experiments are investigated at different magnetic field strengths and compared with the more exact numerical simulations. In contrast to existing analytical treatments, the role of higher order corrections is clearly explained in the context of the MMFT approach leading to a better understanding of the underlying spin physics. Furthermore, the analytical model presented herein provides a general framework for describing coherent and incoherent effects in homonuclear and heteronuclear DQ MAS recoupling experiments.

Algorithms↗

PubMed1982

Aggressive multimodality therapy based on a multicompartmental model of glioblastoma.

Glioblastoma multiforme is composed of multiple cellular compartments with different morphologic, kinetic, metabolic, vascular, and genetic properties. Optimal therapy may consist of a variety of therapeutic strategies designed for individual compartments, administered in close temporal relation. These concepts may turn out to be valid for other solid tumors as well. Microwave-induced hyperthermia can be used to treat metabolically quiescent, relatively hypoxic, nondividing cells (Go) otherwise resistant to radiation and chemotherapy. Similarly, polychemotherapy can treat a broad spectrum of cell types if the blood-brain barrier can be circumvented. Radical surgery, repetitively applied, can be safely used to "set up" experimental agents if the operation microscope and laser are employed. A consecutive series of 74 adult patients with malignant astrocytoma were treated with primary resection, radiation therapy, and 1,3,-bis(2 chloroethyl) 1 nitrosourea chemotherapy. At recurrence, all patients were offered reoperation with the microscope and the laser prior to administration of phase-I agents--hyperthermia via an implantable miniature microwave antenna (6 cases); aziridinylbenzoquinone chemotherapy (13 cases); and blood-brain barrier reversal with dimethyl sulfoxide (DMSO) and polychemotherapy (9 cases). It was concluded that temperatures of 45 degrees C could be safely achieved and human tumors could not efficiently dissipate heat; that DMSO plus drug therapy could be tolerated but blood-brain barrier reversal demonstrated by us in animals could not be shown in humans; and that aggressive multimodality therapy and reoperation could produce a 40% 2-year survival rate for patients younger than 40 years.

Brain Neoplasms↗

PubMed2004

An in vitro model to optimize dose scheduling of multimodal radioimmunotherapy and chemotherapy: effects of p53 expression.

Several reports have appeared on the use of combined radioimmunotherapy (RAIT) and chemotherapy. The choice of drug to use with RAIT and how to space the two treatments has not been completely addressed. Because every patient's cancer presents with a specific molecular phenotype, we hypothesized that it may be necessary to tailor therapy based on specific gene expression. We addressed how the form of expression of a single gene, the p53 tumor suppressor, would impact the choice of agents, as well as sequence and spacing of agents. p53 regulates cell cycle arrest to allow for DNA repair after therapy-induced small DNA damage or induction of apoptosis if damage is great and has been shown to affect chemo- and radiosensitivity of cancer cells. We established 3 stable p53 transfectants of the SKOV-3 p53null parental line (p53(wt), p53(143mut) or p53(273mut)). p53 expression was confirmed using flow cytometry, using the DO1 pan-p53 Ab and the PAb240 anti-p53mut Ab. The colorimetric MTT assay was then used to measure dose-dependent growth inhibition from single modality chemotherapy (doxorubicin, carboplatin, paclitaxel or topotecan) or radioimmunotherapy (90Y-RS-7 IgG anti-EGP1). The % survival vs. log [drug] were plotted to obtain the IC50. We then used a matrix design in which we varied the sequence of the first and second modality of treatment and the spacing between the 2 treatments to determine the most synergistic and antagonistic combinations for the parental SKOV-3 and each of the 3 transfectants. The IC50 for each therapeutic agent varied as a function of the form of p53 expressed. For example, of the 4 lines, the p53wt transfectant was the most resistant to topotecan and the 143mut was the most resistant to carboplatin. The 273mut was quite sensitive to both doxorubicin and paclitaxel, whereas the p53null and wt were not. For multimodal treatments, most combinations of RAIT and chemotherapy resulted in a 30-40% growth inhibition (GI) and were either additive or moderately antagonistic. The 3 best (>60% GI) and 3 worst (<25% GI) combinations were identified and were unique to the parental p53null and to the 3 transfectants. Certain combinations showed clear synergy and others were antagonistic, with the first treatment modality blocking the growth inhibitory effects of the second treatment modality. The form of p53 expressed affects chemosensitivity and radiosensitivity and will influence optimal multimodal therapy with RAIT and chemotherapy and the dose-schedule (sequential with RAIT first or with drug first) when more than 1 agent is used.

Antineoplastic Agents↗

PubMed2004

Calcium and glycolysis mediate multiple bursting modes in pancreatic islets.

Pancreatic islets of Langerhans produce bursts of electrical activity when exposed to stimulatory glucose levels. These bursts often have a regular repeating pattern, with a period of 10-60 s. In some cases, however, the bursts are episodic, clustered into bursts of bursts, which we call compound bursting. Consistent with this are recordings of free Ca2+ concentration, oxygen consumption, mitochondrial membrane potential, and intraislet glucose levels that exhibit very slow oscillations, with faster oscillations superimposed. We describe a new mathematical model of the pancreatic beta-cell that can account for these multimodal patterns. The model includes the feedback of cytosolic Ca2+ onto ion channels that can account for bursting, and a metabolic subsystem that is capable of producing slow oscillations driven by oscillations in glycolysis. This slow rhythm is responsible for the slow mode of compound bursting in the model. We also show that it is possible for glycolytic oscillations alone to drive a very slow form of bursting, which we call "glycolytic bursting." Finally, the model predicts that there is bistability between stationary and oscillatory glycolysis for a range of parameter values. We provide experimental support for this model prediction. Overall, the model can account for a diversity of islet behaviors described in the literature over the past 20 years.

Animals↗

PubMedDate not supplied

Multimodal imaging analysis of tumor progression and bone resorption in a murine cancer model.

OBJECTIVE: This study evaluates the use of multimodal imaging to qualitatively and quantitatively measure tumor progression and bone resorption in a xenotransplanted tumor model of human neuroblastoma. METHODS: Human neuroblastoma cells expressing a luciferase reporter gene were injected into the femur of nu/nu mice. Tumor progression with and without zoledronic acid treatment was monitored using radiographs, D-luciferin-induced luminescence, micro-computer tomography (CT) and micro-magnetic resonance imaging (MRI). RESULTS: We observed a gradual increase in D-luciferin-based bioluminescence concomitant with detectable osteolytic lesions. Tumor growth was inhibited (P=0.003-0.07) with zoledronic acid treatment. Micro-CT analysis in vivo provided a method to quantify bone loss, and its prevention by zoledronic acid. High-resolution MRI images allowed the observation of tumor cells within the bone marrow cavity, as well as distant metastasis. CONCLUSION: Multimodal imaging allows to measure tumor growth and bone resorption simultaneously in vivo and also proved useful in the detection distant metastasis.

Animals↗

PubMed1994

Unexpected radiation protection with 13-cis-retinoic acid plus interferon alpha-2a.

A recent clinical protocol combining retinoic acid, interferon, and radiotherapy for advanced cervical cancer produced proctitis severe enough to necessitate dose reductions. In an attempt to model this biological response to multimodality therapy, we used a murine model to study the response of the colonic epithelium. Mice were treated with retinoic acid (100 micrograms/day) and interferon (3 x 10(4) units/day) for 5 days before undergoing whole-body irradiation. The functional response of the bowel was assessed by the ability to maintain body weight, and reproductive cell survival was quantified by the colon crypt assay. Both assays indicated a moderate protective effect of treatment with retinoic acid and interferon prior to irradiation. Protection factors in the range of 1.1-1.4 were observed.

Animals↗

PubMed2026

Machine learning for population-level risk prediction of future cholangiocarcinoma.

BACKGROUND: The poor prognosis of cholangiocarcinoma (CCA) is largely driven by rapid, asymptomatic disease progression, which usually results in a late diagnosis in the absence of established screening strategies. An early, cost-effective, and universally applicable risk assessment strategy would therefore be valuable. METHODS: We developed machine learning (ML) models on prospective, multimodal data from 487,495 UK Biobank (UKB) participants, of whom 649 developed CCA during follow-up. Data from England (80%) were utilised for ML development via five-fold cross-validation, and then all models were tested on withheld data from Scotland, Wales, and Newcastle (20%). Iterative ablation studies reduced inputs from >150 features across demographic data, lifestyle, health records, blood parameters, genomics, and metabolomics to models built on five and ten routinely available clinical parameters. These were externally validated in the Penn Medicine Biobank (PMBB; n = 2638; 28 CCA), All of Us Research Program (AOU; n = 330,433; 362 CCA), Japan Medical Data Centre Claims Database (JMDC; n = 8,425,522; 723 CCA) and TriNetX (n = 728,886; 1592 CCA). FINDINGS: We show that ML models integrating biliary-disease associated health records and Gamma glutamyltransferase can stratify risk of future CCA. Evaluation on the UKB test set as well as three independent cohorts revealed robust performance and generalisability across ethnicities. We achieved AUROCs of 0.71 [95% CI: 0.703-0.711], 0.77 [95% CI: 0.764-0.778 ], 0.796 [95% CI: 0.795-0.798] and 0.8 [95% CI: 0.794-0.805] for UKB, PMBB, AOU, and JMDC respectively, with respective AUPRCs of 0.014 [95% CI: 0.009-0.018], 0.042 [95% CI: 0.037-0.048], 0.038 [95% CI: 0.033-0.042] and 0.001 [95% CI: 0.001-0.001]. In AOU, application of the Youden J-optimised threshold yielded a number needed to screen of 79. Separate models for intra- and extrahepatic CCA did not improve performance. In line with the pathophysiology, performance declined for longer intervals between assessment and event. A group-level analysis in the TriNetX cohort revealed hazard ratios of up to 82.5 [95% CI: 26.4-257.96]. We provide extensive interpretability results and release all source codes used to develop the presented models. INTERPRETATION: We provide a comprehensive framework for early CCA risk stratification in the general population, identifying key predictors, and demonstrating the potential of data-driven models in personalised screening for hepatobiliary cancer. FUNDING: German Cancer Aid (grant #70115730), Junior Principal Investigator Fellowship programme of RWTH Aachen Excellence strategy.

Humans↗

PubMedDate not supplied

Retrospective fusion of radiographic and MR data for localization of subdural electrodes.

Prior to epilepsy surgery, subdural electrodes are often implanted and monitored for a few days to identify the focus of abnormal electrical activity. During the implantation and subsequent brain resection, there may be uncertainty about the exact location of the electrodes with respect to features of brain anatomy such as specific gyral convolutions or lesions. In experiments with a phantom and patients, implanted electrodes were imaged with multiplanar skull radiographs (or CT scans). After retrospective registration with preimplantation MR data, the electrodes were mapped from these studies onto an MR-derived three-dimensional brain model. The resulting multimodality displays showed the relationship of the electrodes to brain anatomy. In one patient the position of each electrode with respect to a metabolic lesion was also displayed by mapping preimplantation PET data onto the same brain model. This new display of electrode positions may strengthen the interpretation of subdural electrical recordings and thereby reduce uncertainty in planning the resection of epileptic tissue.

Adult↗

PubMed2004

Multimodal classical conditioning of fear: contributions of direct, observational, and verbal experiences to current fears.

The authors propose that a multimodal classical conditioning model be considered when clinicians or clinical researchers study the etiology of fears and anxieties learned by human beings. They argue that fears can be built through the combined effects of direct, observed, and verbally presented classical conditioning trials. Multimodal classical conditioning is offered as an alternative to the three pathways to fear argument prominent in the human fear literature. In contrast to the three pathways position, the authors present theoretical arguments for why "learning by observation" and "learning through the receipt of verbal information" should be considered classical conditioning through observational and verbal modes. The paper includes a demonstration of how data, commonly collected in research on the three pathways to fear, would be studied differently using a multimodal classical conditioning perspective. Finally, the authors discuss implications for assessment, treatment, and prevention of learned fears in humans.

Adolescent↗

PubMed2006

Finite-element stress analysis of a multicomponent model of sheared and focally-adhered endothelial cells.

Hemodynamic forces applied at the apical surface of vascular endothelial cells may be redistributed to and amplified at remote intracellular organelles and protein complexes where they are transduced to biochemical signals. In this study we sought to quantify the effects of cellular material inhomogeneities and discrete attachment points on intracellular stresses resulting from physiological fluid flow. Steady-state shear- and magnetic bead-induced stress, strain, and displacement distributions were determined from finite-element stress analysis of a cell-specific, multicomponent elastic continuum model developed from multimodal fluorescence images of confluent endothelial cell (EC) monolayers and their nuclei. Focal adhesion locations and areas were determined from quantitative total internal reflection fluorescence microscopy and verified using green fluorescence protein-focal adhesion kinase (GFP-FAK). The model predicts that shear stress induces small heterogeneous deformations of the endothelial cell cytoplasm on the order of <100 nm. However, strain and stress were amplified 10-100-fold over apical values in and around the high-modulus nucleus and near focal adhesions (FAs) and stress distributions depended on flow direction. The presence of a 0.4 microm glycocalyx was predicted to increase intracellular stresses by approximately 2-fold. The model of magnetic bead twisting rheometry also predicted heterogeneous stress, strain, and displacement fields resulting from material heterogeneities and FAs. Thus, large differences in moduli between the nucleus and cytoplasm and the juxtaposition of constrained regions (e.g. FAs) and unattached regions provide two mechanisms of stress amplification in sheared endothelial cells. Such phenomena may play a role in subcellular localization of early mechanotransduction events.

Animals↗

PubMed2005

The determination of the size and shape of buried InAs/InP quantum dots by transmission electron microscopy.

Bright-field, diffraction-contrast imaging in the transmission electron microscope has been applied to the determination of the diameter and height populations of a single layer of buried, pure, InAs/InP quantum dots (QDs). Plan-view diffraction contrast from the QDs was observed to increase significantly when the sample was tilted away from the [001] growth direction to near the [111] zone-axis orientation. This added contrast was a result of contributions to the displacement of atoms in a direction perpendicular to the electron beam arising from strain in the growth direction. Since the strain in the growth direction was about an order of magnitude larger than the strain perpendicular to the growth direction, as the sample is tilted away from the [001] zone-axis condition, the larger strain component increases the projected strain thereby increasing the QD contrast in the image. For the sample studied, both of the populations for the QD diameter and the image contrast were observed to be multimodal with the seven peaks in the contrast distribution correlating with seven distinct populations of QDs each differing in height by one monolayer (ML), from 3 to 9MLs. An analysis of the theoretically expected and experimentally observed standard deviations in the Gaussian fits to the QD diameter and height distributions provided an additional constraint in the selection of the optimal model for the multimodal distributions.

Journal Article↗

PubMed2026

Biological Foundation Models for Complex Disease Research and Clinical Translation.

Complex diseases, including cancer, rare genetic disorders, neurodevelopmental and psychiatric conditions, and neurodegenerative diseases, arise from interactions among genetic variation, gene regulation, and cellular states that are difficult to capture using a single data type or biological scale. Biological foundation models address this challenge by treating nucleotides and genes as tokens and learning representations that can be transferred to downstream biomedical and clinical tasks. In this review, we examine two major model classes, genomic sequence foundation models and cell foundation models, and compare their tokenization strategies, model architectures, pretraining objectives, and adaptation methods. We summarize their emerging applications in regulatory variant interpretation, disease-associated cell-state analysis, drug-response prediction, and therapeutic target discovery across complex diseases. We distinguish applications supported by experimental or retrospective validation from those that remain primarily computational or conceptual. We further discuss key challenges to clinical translation, including multimodal data integration, model interpretability, benchmarking, patient-specific prediction, and privacy protection. We highlight future opportunities to integrate biological foundation models with emerging frameworks of medical digital twins, agentic AI, and federated learning. By linking model design to translational goals, this review provides a practical framework for evaluating biological foundation models and their readiness for complex disease research and clinical use.

biological foundation model↗

PubMed2026

Harnessing the Power of Large Language Models for Drug Discovery: A Systematic Review of Current Applications and Future Directions.

INTRODUCTION: The demand for inventive approaches to drug discovery has increased due to the rising costs, time, and failure rates in pharmaceutical research. Large Language Models (LLMs), with their sophisticated natural language processing and generative capabilities, have become potent instruments that have the potential to revolutionize biomedical research. The function of LLMs in different phases of drug development is methodically examined in this article. METHODS: The PRISMA 2020 principles were adhered to in this systematic study. A thorough search for research published between 2018 and 2025 was done using PubMed, Scopus, Web of Science, and Google Scholar. The search terms "large language model," "transformer," "drug discovery," and important sub-domains (such as "de-novo design" and "ADMET") were merged, and two reviewers independently screened the results. Predetermined inclusion and exclusion criteria were used to filter studies for relevance. 98 studies out of the 1,285 records that were initially retrieved met the requirements for the final qualitative synthesis. RESULTS: 98 studies that demonstrated the use of LLMs in various drug discovery domains were found during the review. These covered molecular generation, genomics, protein-ligand modeling, ADME/T and toxicity profiling, drug-target interaction and DTI prediction, and biomedical text mining. 42 different LLM-based tools were mapped, including BioBERT, SciSpacy, Drug- LLM, DNA-BERT, GPT-4, and ChatGPT. Predictive accuracy, hypothesis creation, target prioritization, and multi-modal data integration all showed notable gains with these techniques. DISCUSSION: By providing scalable, precise, and effective solutions for data-driven drug discovery, LLMs are revolutionizing the pharmaceutical industry. They allow for the creation of hypotheses and individualized insights across multi-modal biological data, and they perform better than conventional approaches in a number of subdomains. Improvements in performance were task-dependent; the most consistent gains occurred for biomedical text mining, disease-genedrug relationship mapping and drug-target interaction prediction tasks. Yet most evidence for clinical applications is still derived from retrospective studies and benchmark datasets, suggesting a higher need for prospective validation. CONCLUSION: There is revolutionary potential in incorporating LLMs into drug discovery processes. Clinical translation and regulatory uptake will depend heavily on collaborative validation, ethical deployment, and standardization as models become more multimodal and interpretable. Before normal use, extensive prospective benchmarking and head-to-head comparisons with established chemoinformatics pipelines are necessary.

De novo design↗