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The Operator Era in Pharma has arrived. Artificial intelligence is no longer limited to answering questions or generating drafts. It is beginning to execute real work across pharmaceutical organizations. From screening thousands of research papers and assembling HEOR dossiers to supporting clinical operations and quality processes, AI operators are taking on repetitive, evidence-intensive tasks while…
Overview Every week, safety scientists at pharmaceutical organizations process hundreds of Individual Case Safety Reports (ICSRs) under 15-day regulatory deadlines. Each report may arrive in a different language, reference local trade names, follow a different format, and be subject to a different regulatory jurisdiction. Despite this complexity, the core decision is always the same: does…
Introduction: Rethinking Data Extraction Clinical literature is the lifeblood of pharmaceutical research, but also one of its biggest bottlenecks. That is to say, extracting structured insights from trial publications can require weeks of manual review, as human experts search through dense narratives, tables, and figures. Working in partnership with top-20 pharma manufacturers, we set out…
Introduction: The Limits of “Chat” Two years ago, the pharmaceutical industry, like much of the tech world, was captivated by the arrival of Generative AI. For the first time, researchers could interact with unstructured data, summarizing decades of clinical trial reports in seconds. It was a breakthrough in knowledge retrieval. However, as we moved these…
Overview The field of Life Sciences is grappling with an explosion of data. This crucial information, such as spanning research papers, clinical trial reports, patient records, and even genomic sequences, exists as unstructured text. Transforming this vast textual landscape into actionable insights is a significant challenge. This is where the power of Natural Language Processing…
Systematic literature reviews (SLRs) are the backbone of evidence-based decision-making in life sciences. But not every SLR is submission-related. So, what purpose do these rigorous reviews serve beyond journal publication or HTA submission? CapeStart’s 2024 Literature Review Research Report offers valuable insights into this question, with responses from 79 life sciences professionals actively involved in literature…
Artificial intelligence (AI) has significantly impacted the pharmaceutical business in several ways, from drug discovery and formulation to clinical trials and monitoring for adverse drug reactions. But AI can also help improve pharma manufacturing, distribution, and supply chain management by improving efficiency, safety, quality, and other processes. Here’s how AI can be used to improve…
Artificial intelligence has proven invaluable across many applications in countless industries. But, one of the most promising areas in which AI has recently made an impact is structural biology—in particular molecular dynamics (MD), or the simulation of the makeup and movement of molecules and atoms. Researchers can use powerful AI models to learn more about the structures…
Drug discovery and target identification is a notoriously expensive and slow process: Preclinical drug development (the research stage that precedes clinical trials) can sometimes take more than five years and cost billions of dollars. Even the experimental drugs that make it to clinical trials tend to flame out quickly. Around 90 percent of clinical drug development ultimately…
The pharmaceutical supply chain is incredibly complex: From sourcing and supplying materials to manufacturing and distribution of incredibly sensitive products that could be rendered inactive without the right environmental conditions. This complexity – and the dependence of governments and populations on the pharmaceutical industry’s life-saving products – are why pharma supply chains are so important. …
