RESUMO
Large language models (LLMs) are sophisticated AI-driven models trained on vast sources of natural language data. They are adept at generating responses that closely mimic human conversational patterns. One of the most notable examples is OpenAI's ChatGPT, which has been extensively used across diverse sectors. Despite their flexibility, a significant challenge arises as most users must transmit their data to the servers of companies operating these models. Utilizing ChatGPT or similar models online may inadvertently expose sensitive information to the risk of data breaches. Therefore, implementing LLMs that are open source and smaller in scale within a secure local network becomes a crucial step for organizations where ensuring data privacy and protection has the highest priority, such as regulatory agencies. As a feasibility evaluation, we implemented a series of open-source LLMs within a regulatory agency's local network and assessed their performance on specific tasks involving extracting relevant clinical pharmacology information from regulatory drug labels. Our research shows that some models work well in the context of few- or zero-shot learning, achieving performance comparable, or even better than, neural network models that needed thousands of training samples. One of the models was selected to address a real-world issue of finding intrinsic factors that affect drugs' clinical exposure without any training or fine-tuning. In a dataset of over 700 000 sentences, the model showed a 78.5% accuracy rate. Our work pointed to the possibility of implementing open-source LLMs within a secure local network and using these models to perform various natural language processing tasks when large numbers of training examples are unavailable.
Assuntos
Processamento de Linguagem Natural , Humanos , Redes Neurais de Computação , Aprendizado de MáquinaRESUMO
BACKGROUND: During drug development, it is essential to gather information about the change of clinical exposure of a drug (object) due to the pharmacokinetic (PK) drug-drug interactions (DDIs) with another drug (precipitant). While many natural language processing (NLP) methods for DDI have been published, most were designed to evaluate if (and what kind of) DDI relationships exist in the text, without identifying the direction of DDI (object vs. precipitant drug). Here we present a method for the automatic identification of the directionality of a PK DDI from literature or drug labels. METHODS: We reannotated the Text Analysis Conference (TAC) DDI track 2019 corpus for identifying the direction of a PK DDI and evaluated the performance of a fine-tuned BioBERT model on this task by following the training and validation steps prespecified by TAC. RESULTS: This initial attempt showed the model achieved an F-score of 0.82 in identifying sentences as containing PK DDI and an F-score of 0.97 in identifying object versus precipitant drugs in those sentences. DISCUSSION AND CONCLUSION: Despite a growing list of NLP methods for DDI extraction, most of them use a common set of corpora to perform general purpose tasks (e.g., classifying a sentence into one of several fixed DDI categories). There is a lack of coordination between the drug development and biomedical informatics method development community to develop corpora and methods to perform specific tasks (e.g., extract clinical exposure changes due to PK DDI). We hope that our effort can encourage such a coordination so that more "fit for purpose" NLP methods could be developed and used to facilitate the drug development process.
Assuntos
Aprendizado Profundo , Processamento de Linguagem Natural , Interações Medicamentosas , Mineração de Dados/métodos , IdiomaRESUMO
Despite a rapid increase in pediatric mortality rate from prescription and illicit opioids, there is limited research on the dose-dependent impact of opioids on respiratory depression in children, the leading cause of opioid-associated death. In this article, we extend a previously developed translational model to cover pediatric populations by incorporating age-dependent pharmacokinetic, pharmacodynamic, and physiological changes compared to adults. Our model reproduced previous perioperative clinical findings that adults and children have similar risk of respiratory depression at the same plasma fentanyl concentration when specific endpoints (minute ventilation, CO2 tension in the blood) were used. However, our model points to a potential caveat that, in a perioperative setting, routine use of mechanical ventilation and supplemental oxygen maintained the blood and tissue oxygen partial pressures in patients and prevented the use of oxygen-related endpoints to evaluate the consequences of respiratory depression. In a community setting when such oxygenation procedures are not immediately available, our model suggests that the higher oxygen demand and reduced cerebrovascular reactivity could make children more susceptible to severe hypoxemia and brain hypoxia, even with the same plasma fentanyl concentration as adults. Our work indicates that when developing intervention strategies to protect children from opioid overdose in a community setting, these pediatric-specific factors may need to be considered.
Assuntos
Overdose de Opiáceos , Insuficiência Respiratória , Adulto , Humanos , Criança , Insuficiência Respiratória/induzido quimicamente , Oxigênio , Analgésicos Opioides/efeitos adversos , Fentanila/efeitos adversosRESUMO
Importance: Questions have emerged as to whether standard intranasal naloxone dosing recommendations (ie, 1 dose with readministration every 2-3 minutes if needed) are adequate in the era of illicitly manufactured fentanyl and its derivatives (hereinafter, fentanyl). Objective: To compare naloxone plasma concentrations between different intranasal naloxone repeat dosing strategies and to estimate their effect on fentanyl overdose. Design, Setting, and Participants: This unblinded crossover randomized clinical trial was conducted with healthy participants in a clinical pharmacology unit (Spaulding Clinical Research, West Bend, Wisconsin) in March 2021. Inclusion criteria included age 18 to 55 years, nonsmoking status, and negative test results for the presence of alcohol or drugs of abuse. Data analysis was performed from October 2021 to May 2023. Intervention: Naloxone administered as 1 dose (4 mg/0.1 mL) at 0, 2.5, 5, and 7.5 minutes (test), 2 doses at 0 and 2.5 minutes (test), and 1 dose at 0 and 2.5 minutes (reference). Main Outcomes and Measures: The primary outcome was the first prespecified time with higher naloxone plasma concentration. The secondary outcome was estimated brain hypoxia time following simulated fentanyl overdoses using a physiologic pharmacokinetic-pharmacodynamic model. Naloxone concentrations were compared using paired tests at 3 prespecified times across the 3 groups, and simulation results were summarized using descriptive statistics. Results: This study included 21 participants, and 18 (86%) completed the trial. The median participant age was 34 years (IQR, 27-50 years), and slightly more than half of participants were men (11 [52%]). Compared with 1 naloxone dose at 0 and 2.5 minutes, 1 dose at 0, 2.5, 5, and 7.5 minutes significantly increased naloxone plasma concentration at 10 minutes (7.95 vs 4.42 ng/mL; geometric mean ratio, 1.95 [1-sided 97.8% CI, 1.28-∞]), whereas 2 doses at 0 and 2.5 minutes significantly increased the plasma concentration at 4.5 minutes (2.24 vs 1.23 ng/mL; geometric mean ratio, 1.98 [1-sided 97.8% CI, 1.03-∞]). No drug-related serious adverse events were reported. The median brain hypoxia time after a simulated fentanyl 2.97-mg intravenous bolus was 4.5 minutes (IQR, 2.1-∞ minutes) with 1 naloxone dose at 0 and 2.5 minutes, 4.5 minutes (IQR, 2.1-∞ minutes) with 1 naloxone dose at 0, 2.5, 5, and 7.5 minutes, and 3.7 minutes (IQR, 1.5-∞ minutes) with 2 naloxone doses at 0 and 2.5 minutes. Conclusions and Relevance: In this clinical trial with healthy participants, compared with 1 intranasal naloxone dose administered at 0 and 2.5 minutes, 1 dose at 0, 2.5, 5, and 7.5 minutes significantly increased naloxone plasma concentration at 10 minutes, whereas 2 doses at 0 and 2.5 minutes significantly increased naloxone plasma concentration at 4.5 minutes. Additional research is needed to determine optimal naloxone dosing in the community setting. Trial Registration: ClinicalTrials.gov Identifier: NCT04764630.
Assuntos
Hipóxia Encefálica , Overdose de Opiáceos , Masculino , Humanos , Adolescente , Adulto Jovem , Adulto , Pessoa de Meia-Idade , Feminino , Etanol , Comércio , Fentanila , Naloxona/uso terapêuticoRESUMO
The process of new blood vessel growth (angiogenesis) is highly dynamic, involving complex coordination of multiple cell types. Though the process must carefully unfold over time to generate functional, well-adapted branching networks, we seldom hear about the time-based properties of angiogenesis, despite timing being central to other areas of biology. Here, we present a novel, time-based formulation of endothelial cell behaviour during angiogenesis and discuss a flurry of our recent, integrated in silico/in vivo studies, put in context to the wider literature, which demonstrate that tissue conditions can locally adapt the timing of collective cell behaviours/decisions to grow different vascular network architectures. A growing array of seemingly unrelated 'temporal regulators' have recently been uncovered, including tissue derived factors (e.g. semaphorins or the high levels of VEGF found in cancer) and cellular processes (e.g. asymmetric cell division or filopodia extension) that act to alter the speed of cellular decisions to migrate. We will argue that 'temporal adaptation' provides a novel account of organ/disease-specific vascular morphology and reveals 'timing' as a new target for therapeutics. We therefore propose and explain a conceptual shift towards a 'temporal adaptation' perspective in vascular biology, and indeed other areas of biology where timing remains elusive.This article is part of the themed issue 'Systems morphodynamics: understanding the development of tissue hardware'.
Assuntos
Células Endoteliais/fisiologia , Neovascularização Fisiológica , Animais , HumanosRESUMO
Local synchronization, both prolonged and transient, of oscillatory neuronal behavior in cortical networks plays a fundamental role in many aspects of perception and cognition. Here we study networks of Hindmarsh-Rose neurons with a new type of adaptive coupling, and show that these networks naturally produce both permanent and transient synchronization of local clusters of neurons. These deterministic systems exhibit complex dynamics with 1/fη power spectra, which appears to be a consequence of a novel form of self-organized criticality.
Assuntos
Simulação por Computador , Modelos Neurológicos , Rede Nervosa/fisiologia , Neurônios/fisiologia , Algoritmos , Sincronização Cortical , Análise de Fourier , Humanos , Potenciais da Membrana , Rede Nervosa/citologia , Neurônios/citologiaRESUMO
The asymmetric division of stem or progenitor cells generates daughters with distinct fates and regulates cell diversity during tissue morphogenesis. However, roles for asymmetric division in other more dynamic morphogenetic processes, such as cell migration, have not previously been described. Here we combine zebrafish in vivo experimental and computational approaches to reveal that heterogeneity introduced by asymmetric division generates multicellular polarity that drives coordinated collective cell migration in angiogenesis. We find that asymmetric positioning of the mitotic spindle during endothelial tip cell division generates daughters of distinct size with discrete 'tip' or 'stalk' thresholds of pro-migratory Vegfr signalling. Consequently, post-mitotic Vegfr asymmetry drives Dll4/Notch-independent self-organization of daughters into leading tip or trailing stalk cells, and disruption of asymmetry randomizes daughter tip/stalk selection. Thus, asymmetric division seamlessly integrates cell proliferation with collective migration, and, as such, may facilitate growth of other collectively migrating tissues during development, regeneration and cancer invasion.