<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>ClinLit AI blog</title><description>Reports from the clinical trial registry and the literature, guides to clinical research, and real questions answered with citations.</description><link>https://clinlit.com/</link><item><title>How to benchmark a clinical trial design against earlier trials and their protocols: a repeatable method</title><link>https://clinlit.com/blog/how-to-benchmark-a-clinical-trial-design/</link><guid isPermaLink="true">https://clinlit.com/blog/how-to-benchmark-a-clinical-trial-design/</guid><description>A step-by-step method for checking a trial design&apos;s assumptions against earlier trials, their protocols and results, with questions to reuse and the traps to avoid.</description><pubDate>Tue, 10 Nov 2026 00:00:00 GMT</pubDate><category>how-to</category><category>trial design</category><category>sample size</category><category>protocols</category><category>statistical analysis plans</category><category>ClinicalTrials.gov</category><category>PubMed</category></item><item><title>How to design a phase 2b MASH trial: lessons from 219 trials and their protocols</title><link>https://clinlit.com/blog/how-to-design-a-phase-2b-mash-trial/</link><guid isPermaLink="true">https://clinlit.com/blog/how-to-design-a-phase-2b-mash-trial/</guid><description>Placebo response from 2% to 33%, screen failure up to 87%: what 219 phase 2 MASH trials and six protocols show about endpoints, sample size and biopsies.</description><pubDate>Tue, 10 Nov 2026 00:00:00 GMT</pubDate><category>MASH</category><category>NASH</category><category>trial design</category><category>sample size</category><category>placebo response</category><category>screen failure</category><category>protocols</category><category>ClinicalTrials.gov</category></item><item><title>How accurate is ClinLit AI? 50 test questions, checked against the sources</title><link>https://clinlit.com/blog/how-accurate-is-clinlit-ai-accuracy-audit/</link><guid isPermaLink="true">https://clinlit.com/blog/how-accurate-is-clinlit-ai-accuracy-audit/</guid><description>We tested ClinLit AI on 50 new questions and checked each answer against ClinicalTrials.gov, PubMed and FDA sources. The results, with every error listed.</description><pubDate>Mon, 09 Nov 2026 00:00:00 GMT</pubDate><category>accuracy</category><category>evaluation</category><category>AI agents</category><category>ClinicalTrials.gov</category><category>PubMed</category><category>FDA</category><category>FAERS</category></item><item><title>Eli Lilly R&amp;D profile, November 2026: pipeline, trials and peer comparison</title><link>https://clinlit.com/blog/eli-lilly-rd-profile-november-2026/</link><guid isPermaLink="true">https://clinlit.com/blog/eli-lilly-rd-profile-november-2026/</guid><description>Eli Lilly&apos;s clinical pipeline as of 7 November 2026: 240 active trials, its late-stage drugs, readouts due, FDA approvals, and how it compares with four peers.</description><pubDate>Sun, 08 Nov 2026 00:00:00 GMT</pubDate><category>company profile</category><category>Eli Lilly</category><category>pipeline</category><category>competitive intelligence</category><category>ClinicalTrials.gov</category><category>Drugs@FDA</category></item><item><title>How to build a pharma company R&amp;D profile from public data: a repeatable method</title><link>https://clinlit.com/blog/how-to-build-a-pharma-company-rd-profile/</link><guid isPermaLink="true">https://clinlit.com/blog/how-to-build-a-pharma-company-rd-profile/</guid><description>A step-by-step method for profiling a drug company&apos;s pipeline, trials, FDA record and peers from public data, with questions to reuse and the traps to check.</description><pubDate>Sun, 08 Nov 2026 00:00:00 GMT</pubDate><category>how-to</category><category>company profile</category><category>pipeline analysis</category><category>competitive intelligence</category><category>ClinicalTrials.gov</category><category>Drugs@FDA</category></item><item><title>Cleaning openFDA data: how we linked FAERS, drug labels and approvals to trials and PubMed</title><link>https://clinlit.com/blog/cleaning-openfda-faers-and-drug-label-data/</link><guid isPermaLink="true">https://clinlit.com/blog/cleaning-openfda-faers-and-drug-label-data/</guid><description>What it took to turn openFDA&apos;s FAERS reports, drug labels and approvals into linked, searchable data: the problems we hit, the fixes, and how we checked them.</description><pubDate>Sun, 25 Oct 2026 00:00:00 GMT</pubDate><category>openFDA</category><category>FAERS</category><category>drug labels</category><category>SPL</category><category>UNII</category><category>Drugs@FDA</category><category>data quality</category><category>pharmacovigilance</category></item><item><title>GLP-1 drug side effects in FAERS: which adverse events are reported disproportionately</title><link>https://clinlit.com/blog/glp-1-adverse-events-faers/</link><guid isPermaLink="true">https://clinlit.com/blog/glp-1-adverse-events-faers/</guid><description>Ten years of serious FDA adverse event reports for semaglutide, tirzepatide and four other GLP-1 drugs: what stands out, from pancreatitis to NAION, and what it can&apos;t tell you.</description><pubDate>Sat, 24 Oct 2026 00:00:00 GMT</pubDate><category>FAERS</category><category>pharmacovigilance</category><category>GLP-1</category><category>semaglutide</category><category>tirzepatide</category><category>pancreatitis</category><category>gastroparesis</category><category>NAION</category><category>drug labels</category></item><item><title>Which clinical trials share their protocols? What 100,000 completed trials show</title><link>https://clinlit.com/blog/which-clinical-trials-share-protocols-and-saps/</link><guid isPermaLink="true">https://clinlit.com/blog/which-clinical-trials-share-protocols-and-saps/</guid><description>Only 27% of recently completed trials have posted a protocol, SAP or consent form on ClinicalTrials.gov, and 46% have left no public trace. Who shares, who doesn&apos;t, and why.</description><pubDate>Wed, 21 Oct 2026 00:00:00 GMT</pubDate><category>ClinicalTrials.gov</category><category>trial protocols</category><category>statistical analysis plans</category><category>informed consent</category><category>transparency</category><category>FDAAA</category><category>PubMed</category></item><item><title>Beyond diabetes and obesity: where GLP-1 drugs are being tested in 2026</title><link>https://clinlit.com/blog/glp-1-clinical-trials-beyond-diabetes-obesity/</link><guid isPermaLink="true">https://clinlit.com/blog/glp-1-clinical-trials-beyond-diabetes-obesity/</guid><description>340 trials test GLP-1 drugs in diseases other than diabetes and obesity, from heart failure and MASH to alcohol use and cancer. The data, the trials and their design.</description><pubDate>Tue, 20 Oct 2026 00:00:00 GMT</pubDate><category>GLP-1</category><category>semaglutide</category><category>tirzepatide</category><category>trial design</category><category>clinical trial landscape</category></item><item><title>How we researched GLP-1 trials with ClinLit AI: questions, queries and checks</title><link>https://clinlit.com/blog/how-we-researched-glp-1-trials-with-clinlit-ai/</link><guid isPermaLink="true">https://clinlit.com/blog/how-we-researched-glp-1-trials-with-clinlit-ai/</guid><description>A step-by-step walkthrough of using ClinLit AI to analyse ClinicalTrials.gov, trial protocols and PubMed: the questions we asked, the SQL it ran and how we checked it.</description><pubDate>Tue, 20 Oct 2026 00:00:00 GMT</pubDate><category>how-to</category><category>ClinicalTrials.gov</category><category>AACT</category><category>PubMed</category><category>trial protocols</category><category>GLP-1</category></item></channel></rss>