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		<title>EvidAI — AI-Powered Systematic Literature Review</title>
		<link>https://zorost.com/projects/evidai/</link>
		
		<dc:creator><![CDATA[Zorost Intelligence]]></dc:creator>
		<pubDate>Wed, 20 May 2026 19:25:31 +0000</pubDate>
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					<description><![CDATA[<p>AI-native systematic literature review. EvidAI compresses 12-18 month manual reviews into weeks with multi-agent screening, PRISMA-compliant artifacts, and living-review monitoring.</p>
<p>The post <a href="https://zorost.com/projects/evidai/">EvidAI — AI-Powered Systematic Literature Review</a> appeared first on <a href="https://zorost.com">Zorost Intelligence | AI, Cloud &amp; Data Experts</a>.</p>
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										<content:encoded><![CDATA[<p><strong>EvidAI is an AI-native systematic literature review platform.</strong> It runs the entire workflow — from protocol design through database search, deduplication, multi-stage screening, data extraction, quality appraisal, evidence synthesis, and manuscript-ready output — at a fraction of the time and cost of traditional reviews, while preserving the rigor that regulators, payers, and guideline bodies expect.</p>
<p>It is the kind of platform that turns a 12-to-18-month, six-figure systematic review into a multi-week project that still meets PRISMA standards and is defensible to a critical peer reviewer.</p>
<h2 id="challenge">The challenge</h2>
<p>Every major clinical, regulatory, formulary, and guideline decision depends on a systematic review of the evidence base. Done correctly, that review takes 12 to 18 months, consumes thousands of person-hours, and costs hundreds of thousands of dollars. Done quickly, it cuts corners that show up in reviewer comments, audit findings, or — worse — patient outcomes.</p>
<p>The bottleneck is not literature search. The bottleneck is the human pipeline that follows: two reviewers screening tens of thousands of titles, extracting data into spreadsheets, arguing about risk of bias, and re-running everything when a new paper drops.</p>
<h2 id="status-quo">What the rest of the industry does</h2>
<ul>
<li><strong>Workflow tools</strong> organize the human pipeline in a shared interface. They make collaboration easier; they do not actually do the analytical work.</li>
<li><strong>Screening assistants</strong> use a single model to suggest include/exclude decisions for titles and abstracts. Helpful, but limited to one stage of the workflow and one analytical lens.</li>
<li><strong>Consultancies and CROs</strong> deliver full reviews manually. They produce excellent work; they are slow and expensive, and their methodology lives in their analysts&#8217; heads, not in software.</li>
</ul>
<h2 id="advantage">The Zorost advantage</h2>
<ul>
<li><strong>Full workflow, not a point tool.</strong> EvidAI covers the entire systematic-review chain in one platform. Most competitors automate one stage and leave the others on a spreadsheet.</li>
<li><strong>Multi-agent screening consensus.</strong> Instead of a single model deciding inclusion, EvidAI runs several independent analytical agents and routes disagreements to a human reviewer with full audit trail. That is what gets us into the high-90s range of reviewer-agreement accuracy.</li>
<li><strong>PRISMA-grade artifacts.</strong> Risk-of-bias assessments, GRADE certainty ratings, PRISMA flow diagrams, meta-analytic forest plots, and methodology appendices come out of the platform, not out of a manual rewrite.</li>
<li><strong>Living reviews as a first-class object.</strong> A traditional review is a snapshot. EvidAI treats every review as a continuously monitored object that re-alerts the team when new evidence might change a conclusion.</li>
<li><strong>Federated multi-database search.</strong> Coverage across biomedical, clinical-trial, regulatory, and gray-literature sources in one query, with intelligent deduplication.</li>
</ul>
<h2 id="approach">How we approach it</h2>
<p>EvidAI runs a multi-agent pipeline. Each agent is specialized for a stage — protocol drafting, search-string construction, abstract screening, full-text screening, data extraction, risk-of-bias appraisal, GRADE certainty, and synthesis. The agents do not vote on each other&#8217;s outputs; they run in parallel, surface disagreements, and human reviewers adjudicate, with every decision logged for audit.</p>
<p>The synthesis layer goes beyond search-and-summarize. It produces formal evidence tables, computes meta-analytic effect estimates where appropriate, and generates the methodology and limitations text in a structure that matches regulatory and guideline expectations.</p>
<p>Living-review mode is what we are most excited about. Once a review is published, EvidAI continues to monitor the literature, evaluates each new paper against the review&#8217;s eligibility criteria, and notifies the team when an update could materially change a conclusion.</p>
<h2 id="capabilities">Capability categories</h2>
<ul>
<li><strong>Protocol &amp; search</strong> — PICO-driven protocol drafting and federated search across the major biomedical, regulatory, and gray-literature databases.</li>
<li><strong>Screening</strong> — multi-agent title/abstract and full-text screening with consensus voting and reviewer adjudication.</li>
<li><strong>Extraction</strong> — structured data extraction with field-level provenance back to the source paper.</li>
<li><strong>Quality appraisal</strong> — risk-of-bias and GRADE certainty workflows aligned with current standards.</li>
<li><strong>Synthesis</strong> — evidence tables, meta-analysis, PRISMA flow, and manuscript-ready methodology.</li>
<li><strong>Living reviews</strong> — continuous monitoring with conclusion-change alerts.</li>
<li><strong>Enterprise &amp; audit</strong> — role-based access, decision logs, and a deployment posture suitable for regulated environments.</li>
</ul>
<h2 id="who-its-for">Who it is for</h2>
<ul>
<li>Pharmaceutical R&amp;D, medical affairs, and regulatory evidence teams.</li>
<li>Contract research organizations and health-economics consultancies.</li>
<li>Health-technology assessment bodies and payer evidence teams.</li>
<li>Clinical guideline developers and academic medical centers.</li>
</ul>
<h2 id="faq">Frequently asked questions</h2>
<h3>Is EvidAI a chat-with-papers tool?</h3>
<p>No. EvidAI is a full systematic-review platform. The conversational interface is one feature on top of a methodology-grade pipeline.</p>
<h3>Will it generate citations and methodology text?</h3>
<p>Yes. Methodology, PRISMA diagrams, evidence tables, and limitation sections come out of the platform ready for review by the human authors.</p>
<h3>Can it be deployed for regulated use?</h3>
<p>Yes. EvidAI supports tenant isolation, full audit logging, role-based access, and private deployment for organizations with regulatory or data-residency requirements.</p>
<h2 id="get-in-touch">See it in action</h2>
<p>If your team is evaluating this category and you want to see how we think about the problem, we are happy to share a working demo, a technical briefing, or a proof-of-value engagement. <a href="https://zorost.com/contacts/">Get in touch with Zorost Intelligence</a> and tell us what you are trying to solve.</p>
<p><em>Part of the <a href="https://zorost.com/ai-lab/">Zorost Platforms portfolio</a> — production-grade AI products built on top of our agentic engineering and cloud-modernization practice.</em></p>
<p>The post <a href="https://zorost.com/projects/evidai/">EvidAI — AI-Powered Systematic Literature Review</a> appeared first on <a href="https://zorost.com">Zorost Intelligence | AI, Cloud &amp; Data Experts</a>.</p>
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