Tootfinder

Process-Informed Forecasting of Complex Thermal Dynamics in Pharmaceutical Manufacturing
Ramona Rubini, Siavash Khodakarami, Aniruddha Bora, George Em Karniadakis, Michele Dassisti
https://arxiv.org/abs/2509.20349

Process-Informed Forecasting of Complex Thermal Dynamics in Pharmaceutical Manufacturing
Accurate time-series forecasting for complex physical systems is the backbone of modern industrial monitoring and control. While deep learning models excel at capturing complex dynamics, currently, their deployment is limited due to physical inconsistency and robustness, hence constraining their reliability in regulated environments. We introduce process-informed forecasting (PIF) models for temperature in pharmaceutical lyophilization. We investigate a wide range of models, from classical ones…

Implementing Zero Trust Architecture to Enhance Security and Resilience in the Pharmaceutical Supply Chain
Saeid Ghasemshirazi, Ghazaleh Shirvani, Marziye Ranjbar Tavakoli, Bahar Ghaedi, Mohammad Amin Langarizadeh
https://arxiv.org/abs/2508.15776

Implementing Zero Trust Architecture to Enhance Security and Resilience in the Pharmaceutical Supply Chain
The pharmaceutical supply chain faces escalating cybersecurity challenges threatening patient safety and operational continuity. This paper examines the transformative potential of zero trust architecture for enhancing security and resilience within this critical ecosystem. We explore the challenges posed by data breaches, counterfeiting, and disruptions and introduce the principles of continuous verification, least-privilege access, and data-centric security inherent in zero trust. Real-world …

Modeling for the Growth of Unorganized Retailing in the Presence of Organized and E-Retailing in Indian Pharmaceutical Industry
Koushik Mondal, Balagopal G Menon, Sunil Sahadev
https://arxiv.org/abs/2507.17023

Modeling for the Growth of Unorganized Retailing in the Presence of Organized and E-Retailing in Indian Pharmaceutical Industry
The present study considers the rural pharmaceutical retail sector in India, where the arrival of organized retailers and e-retailers is testing the survival strategies of unorganized retailers. Grounded in a field investigation of the Indian pharmaceutical retail sector, this study integrates primary data collection, consumer conjoint analysis and design of experiments to develop an empirically grounded agent-based simulation of multi-channel competition among unorganized, organized and e-phar…

Crosslisted article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Implementing Zero Trust Architecture to Enhance Security and Resilience in the Pharmaceutical Sup...
Ghasemshirazi, Shirvani, Tavakoli, Ghaedi, Langarizadeh

When you see a “.aspx” details link in a pharmaceutical commercial on TV as a #dotnet developer.

A Quantum Approach for Optimal Transient Control in Network-Based Epidemic Models
Deborah Volpe, Giacomo Orlandi, Mattia Boggio, Carlo Novara, Lorenzo Zino, Giovanna Turvani
https://arxiv.org/abs/2507.15989

A Quantum Approach for Optimal Transient Control in Network-Based Epidemic Models
Effective epidemic control is crucial for mitigating the spread of infectious diseases, particularly when pharmaceutical interventions such as vaccines or treatments are limited. Non-pharmaceutical strategies, including mobility restrictions, are key in reducing transmission rates but require careful optimization to balance public health benefits and socioeconomic costs. Quantum computing is emerging as a powerful tool for solving complex optimization problems that are intractable for classical…

Technical Implementation of Tippy: Multi-Agent Architecture and System Design for Drug Discovery Laboratory Automation
Yao Fehlis, Charles Crain, Aidan Jensen, Michael Watson, James Juhasz, Paul Mandel, Betty Liu, Shawn Mahon, Daren Wilson, Nick Lynch-Jonely, Ben Leedom, David Fuller
https://arxiv.org/abs/2507.17852

Technical Implementation of Tippy: Multi-Agent Architecture and System Design for Drug Discovery Laboratory Automation
Building on the conceptual framework presented in our previous work on agentic AI for pharmaceutical research, this paper provides a comprehensive technical analysis of Tippy's multi-agent system implementation for drug discovery laboratory automation. We present a distributed microservices architecture featuring five specialized agents (Supervisor, Molecule, Lab, Analysis, and Report) that coordinate through OpenAI Agents SDK orchestration and access laboratory tools via the Model Context Prot…

China wants foreign businesses to invest more in the country -- but recent actions taken against foreign executives are sending a chill.
⭐️Chinese authorities have blocked a U.S.-based Wells Fargo banker from returning home,
⭐️and separately sentenced a Japanese executive to more than three years’ imprisonment for espionage.
Though few details of the cases have been made known, they are a reminder of China’s expansive security apparatus
and what to some executives, bu…

China Exit Ban on Wells Fargo Executive Stokes Foreign Business Anxiety
A Wells Fargo banker was blocked from leaving and a Japanese pharmaceutical executive was imprisoned, even as Beijing tries to court overseas investors.

Comment on "Average Hazard as Harmonic Mean" by Chiba
Hajime Uno, Lu Tian, Miki Horiguchi, Satoshi Hattori
https://arxiv.org/abs/2507.15985 https…

Comment on "Average Hazard as Harmonic Mean" by Chiba
In a recent article published in Pharmaceutical Statistics, Chiba proposed a reinterpretation of the average hazard as a harmonic mean of the hazard function and questioned the validity of the Kaplan-Meier plug-in estimator when the truncation time does not coincide with an observed event time. In this commentary, we examine the arguments presented and highlight several points that warrant clarification. Through simulation studies, we further show that the plug-in estimator provides reliable es…

Toward Routine CSP of Pharmaceuticals: A Fully Automated Protocol Using Neural Network Potentials
Zachary L. Glick, Derek P. Metcalf, Scott F. Swarthout
https://arxiv.org/abs/2507.16218

Toward Routine CSP of Pharmaceuticals: A Fully Automated Protocol Using Neural Network Potentials
Crystal structure prediction (CSP) is a useful tool in pharmaceutical development for identifying and assessing risks associated with polymorphism, yet widespread adoption has been hindered by high computational costs and the need for both manual specification and expert knowledge to achieve useful results. Here, we introduce a fully automated, high-throughput CSP protocol designed to overcome these barriers. The protocol's efficiency is driven by Lavo-NN, a novel neural network potential (NNP)…

tl;dr:
PBMs make kickback deals with pharmaceutical manufacturers to keep branded drugs profitable. https://mastodon.social/@blogdiva/115216099306903312

Computational design of personalized drugs via robust optimization under uncertainty
Rabia Altunay, Jarkko Suuronen, Eero Immonen, Lassi Roininen, Jari H\"am\"al\"ainen
https://arxiv.org/abs/2507.16470

Computational design of personalized drugs via robust optimization under uncertainty
Effective disease treatment often requires precise control of the release of the active pharmaceutical ingredient (API). In this work, we present a computational inverse design approach to determine the optimal drug composition that yields a target release profile. We assume that the drug release is governed by the Noyes-Whitney model, meaning that dissolution occurs at the surface of the drug. Our inverse design method is based on topology optimization. The method optimizes the drug compositio…

Who Pays, Who Benefits? Producer-Insurer Games in Life-Saving Medicines
Delia Coculescu, Maximilian Janisch, Thomas Leh\'ericy
https://arxiv.org/abs/2509.16125 https://

Who Pays, Who Benefits? Producer-Insurer Games in Life-Saving Medicines
Pharmaceutical markets for life-saving therapies combine monopoly power with insurance coverage. We build a tractable sequential game in which a patent-holder chooses the drug price, a profit-maximising insurer sets its premium, and a population of heterogeneous agents decide whether to insure and, conditional on diagnosis, whether to purchase treatment. Two sufficient statistics - subjective illness probability and reservation price - capture heterogeneity and nest risk-aversion and liquidity-…

Drug development company Inotiv reports ransomware attack to SEC https://therecord.media/drug-development-innotiv-ransomware-sec

Pharmaceutical company Eversana acquires Waltz Health, which provides drug price-comparison software to insurance companies, creating an entity valued at $6B (John Tozzi/Bloomberg)
https://www.bloomberg.com/news/articles/20

Robert F. Kennedy Jr., the health secretary and a longtime vaccine critic,
announced in a statement Tuesday that
❌ $500 million worth of vaccine development projects -- all using mRNA technology -- will be halted.
The projects — 22 of them — are being led by some of the nation’s leading pharmaceutical companies like Pfizer and Moderna to prevent flu, COVID-19 and H5N1 infections

RFK Jr. pulls funding for vaccines being developed to fight respiratory viruses
The projects — 22 of them — are being led by some of the nation’s leading pharmaceutical companies like Pfizer and Moderna to prevent flu, COVID-19 and H5N1 infections.

Quantum Inspired Legal Tech Environmental Integration for Emergency Pharmaceutical Logistics with Entropy Modulated Collapse and Multilevel Governance
Ruicheng Li, Jingxu Wu
https://arxiv.org/abs/2508.08286

Quantum Inspired Legal Tech Environmental Integration for Emergency Pharmaceutical Logistics with Entropy Modulated Collapse and Multilevel Governance
Emergency pharmaceutical logistics during rapid-onset disasters must balance timeliness, legal compliance, and environmental uncertainty. We present a hybrid framework that co-designs quantum-inspired decision dynamics, embedded legal constraints, and blockchain-verified environmental feedback. Candidate routes are modeled as a superposed state whose collapse is governed by entropy modulation-delaying commitment under ambiguity and accelerating resolution when coherent signals emerge. Legal sta…

Retrieval Augmented Large Language Model System for Comprehensive Drug Contraindications
Byeonghun Bang, Jongsuk Yoon, Dong-Jin Chang, Seho Park, Yong Oh Lee
https://arxiv.org/abs/2508.06145

Retrieval Augmented Large Language Model System for Comprehensive Drug Contraindications
The versatility of large language models (LLMs) has been explored across various sectors, but their application in healthcare poses challenges, particularly in the domain of pharmaceutical contraindications where accurate and reliable information is required. This study enhances the capability of LLMs to address contraindications effectively by implementing a Retrieval Augmented Generation (RAG) pipeline. Utilizing OpenAI's GPT-4o-mini as the base model, and the text-embedding-3-small model for…

Mechanical characterization of pharmaceutical powders and correlation with their behavior during grinding
Laura Baraldi, Davide De Angelis, Roberto Bosi, Roberto Pennini, Irene Bassanetti, Andrea Benassi, Guido Enrico Bellazzi
https://arxiv.org/abs/2508.02767

Mechanical characterization of pharmaceutical powders and correlation with their behavior during grinding
Controlling the size of powder particles is pivotal in the design of many pharmaceutical forms and the related manufacturing processes and plants. One of the most common techniques for particle size reduction in process industry is powder milling, whose efficiency relates to the mechanical properties of powder particles themselves. In this work, we first characterize the elastic and plastic response of different pharmaceutical powders by measuring their Young modulus, the hardness and the britt…

MCPmed: A Call for MCP-Enabled Bioinformatics Web Services for LLM-Driven Discovery
Matthias Flotho (Chair for Clinical Bioinformatics, Center for Bioinformatics, Saarland University, Germany, Helmholtz Institute for Pharmaceutical Research Saarland), Ian Ferenc Diks (Chair for Clinical Bioinformatics, Center for Bioinformatics, Saarland University, Germany, Helmholtz Institute for Pharmaceutical Research Saarland), Philipp Flotho (Chair for Clinical Bioinformatics, Center for Bioinfor…

MCPmed: A Call for MCP-Enabled Bioinformatics Web Services for LLM-Driven Discovery
Bioinformatics web servers are critical resources in modern biomedical research, facilitating interactive exploration of datasets through custom-built interfaces with rich visualization capabilities. However, this human-centric design limits machine readability for large language models (LLMs) and deep research agents. We address this gap by adapting the Model Context Protocol (MCP) to bioinformatics web server backends - a standardized, machine-actionable layer that explicitly associates webse…

Investigating Forecasting Models for Pandemic Infections Using Heterogeneous Data Sources: A 2-year Study with COVID-19
Zacharias Komodromos, Kleanthis Malialis, Panayiotis Kolios
https://arxiv.org/abs/2507.12966

Investigating Forecasting Models for Pandemic Infections Using Heterogeneous Data Sources: A 2-year Study with COVID-19
Emerging in December 2019, the COVID-19 pandemic caused widespread health, economic, and social disruptions. Rapid global transmission overwhelmed healthcare systems, resulting in high infection rates, hospitalisations, and fatalities. To minimise the spread, governments implemented several non-pharmaceutical interventions like lockdowns and travel restrictions. While effective in controlling transmission, these measures also posed significant economic and societal challenges. Although the WHO …

“Today, we’re doing copper,” Trump said during a Cabinet meeting at the White House.
“I believe the tariff on copper, we’re going to make it 50%.” He did not say specifically when that tariff would take effect
Trump also said he would soon announce tariffs “at a very, very high rate -- like 200%,”
on pharmaceutical imports.
And we all hang on the words coming out of his mouth, despite knowing that they were ripped from his ass, without passing though his brain

Trump says he will impose 50% tariff on copper imports

How to use quantum computers for biomolecular free energies
Jakob G\"unther, Thomas Weymuth, Moritz Bensberg, Freek Witteveen, Matthew S. Teynor, F. Emil Thomasen, Valentina Sora, William Bro-J{\o}rgensen, Raphael T. Husistein, Mihael Erakovic, Marek Miller, Leah Weisburn, Minsik Cho, Marco Eckhoff, Aram W. Harrow, Anders Krogh, Troy Van Voorhis, Kresten Lindorff-Larsen, Gemma Solomon, Markus Reiher, Matthias Christandl

How to use quantum computers for biomolecular free energies
Free energy calculations are at the heart of physics-based analyses of biochemical processes. They allow us to quantify molecular recognition mechanisms, which determine a wide range of biological phenomena from how cells send and receive signals to how pharmaceutical compounds can be used to treat diseases. Quantitative and predictive free energy calculations require computational models that accurately capture both the varied and intricate electronic interactions between molecules as well as …

Swarm Intelligence for Chemical Reaction Optimisation
R\'emi Schlama, Joshua W. Sin, Ryan P. Burwood, Kurt P\"untener, Raphael Bigler, Philippe Schwaller
https://arxiv.org/abs/2509.11798

Swarm Intelligence for Chemical Reaction Optimisation
Chemical reaction optimisation is essential for synthetic chemistry and pharmaceutical development, demanding the extensive exploration of many reaction parameters to achieve efficient and sustainable processes. We report $α$-PSO, a novel nature-inspired metaheuristic algorithm that augments canonical particle swarm optimisation (PSO) with machine learning (ML) for parallel reaction optimisation. Unlike black-box ML approaches that obscure decision-making processes, $α$-PSO uses mechanistical…

Designing cultured tissue moulds using evolutionary strategies
Allison E. Andrews, Hugh Dickinson, James P. Hague
https://arxiv.org/abs/2508.00769 https://…

Designing cultured tissue moulds using evolutionary strategies
There is an unmet need for artificial intelligence techniques that can speed up the design of growth strategies for cultured tissues. Cultured tissue is increasingly important for a range of applications such as cultivated meat, pharmaceutical assays and regenerative medicine. In this paper, we introduce a method based around evolutionary strategies, machine learning and biophysical simulations that can be used to speed up the process of identifying new tissue growth strategies for these divers…

Amid turmoil at the Centers for Disease Control and Prevention,
Former President Trump on Monday called on pharmaceutical companies to "justify the success" of their COVID vaccines.
"I have been shown information from Pfizer, and others, that is extraordinary, but they never seem to show those results to the public.
Why not???
They go off to the next 'hunt' and let everyone rip themselves apart,
including Bobby Kennedy Jr. and CDC,
tr…

ShortageSim: Simulating Drug Shortages under Information Asymmetry
Mingxuan Cui, Yilan Jiang, Duo Zhou, Cheng Qian, Yuji Zhang, Qiong Wang
https://arxiv.org/abs/2509.01813 https…

ShortageSim: Simulating Drug Shortages under Information Asymmetry
Drug shortages pose critical risks to patient care and healthcare systems worldwide, yet the effectiveness of regulatory interventions remains poorly understood due to fundamental information asymmetries in pharmaceutical supply chains. We present \textbf{ShortageSim}, the first Large Language Model (LLM)-based multi-agent simulation framework that captures the complex, strategic interactions between drug manufacturers, institutional buyers, and regulatory agencies in response to shortage alert…