AI Clinical Research Advisor is a clinical methodologist that helps teams design, review, and de-risk human studies from first-in-human through pivotal trials. Unlike generic chatbots that skip estimands and site feasibility, this agent treats protocol, GCP, and operations as one problem. Built on Jenova, it combines OpenAI, Anthropic, Google, and more with tools for literature and protocol documents. It does not file INDs or CTAs and is not a substitute for regulatory counsel.
Clinical Research Advisor recommends a trial design that fits the research question, regulator, and what sites can actually run—not a fashionable Phase 3 shell. Parallel-group randomization remains the confirmatory default when it is the honest answer; the AI also lays out when crossover, factorial, cluster, non-inferiority, platform, basket, pragmatic, decentralized, or externally controlled designs are a better fit, and what bias, power, or regulatory acceptance you are trading. Attach prevalence, competing-trial, and visit-burden notes from Google Drive or Dropbox so the recommendation reflects enrollment reality rather than a template sample size.
Clinical Research Advisor reviews protocol drafts for estimands, endpoints, multiplicity, missing data, and internal contradictions against ICH E6(R3) expectations for a clear, operationally feasible protocol. The critique is structural, not copy-editing: objectives, bias-control measures, stopping rules, and how intercurrent events will be handled have to line up with the analysis plan.
Paste a protocol section, SAP outline, or informed-consent draft and the review stays in the same thread as the design decision that produced it.
Clinical Research Advisor maps FDA, EMA, PMDA, NMPA, and ICH expectations before a protocol is locked. US programs are framed around IND, NDA/BLA, and device pathways; EU programs are framed around the Clinical Trials Regulation and CTIS multinational assessment, including what a coordinated review will not tolerate even when the science is sound. The AI separates pre-IND from scientific advice, orphan and expedited designations, and when real-world evidence is a supplement rather than a substitute for randomization—so a Phase 2 protocol is not gold-plated into a label-enabling trial it cannot support. When a question turns on a date, fee, portal, or newly revised guideline, search tools are used to check current positions rather than last year’s PDF.
Clinical Research Advisor pressure-tests recruitment, visit burden, consent, DSMB architecture, and SAE/SUSAR reporting so a scientifically elegant protocol is still executable at the site. Over-restrictive eligibility, unvalidated digital endpoints, missing quality-tolerance limits, and eConsent language that will not survive an IRB or a participant reading at a general-public level are treated as design defects, not appendix items.
The AI will not file to FDA ESG, CTIS, or an ethics committee. It will tell you what those reviewers are likely to ask, and what to fix before you spend a cycle finding out the hard way.
| Traditional Approach | Clinical Research Advisor |
|---|---|
| Sequential stats, writing, and operations handoffs | One science, GCP, and feasibility conversation |
| Template protocols that trigger post-FPI amendments | Early flags on eligibility and visit burden |
| Chatbot drafts that skip ICH E9(R1) estimands | Estimand-first ITT, per-protocol, and sensitivity options |
| Isolated reading of FDA and EMA guidance | Cross-walk of FDA, EMA, and ICH |
Unlimited Memory vs. Chatbot Amnesia
A generic chatbot loses the treatment-policy estimand you locked last week, then the SAP, sample size, and intercurrent-event rules drift apart. Clinical Research Advisor retains the indication, comparator, locked endpoints, struck eligibility criteria, jurisdiction, and amendment logic across sessions so a later DSMB, consent, or safety question is answered against the protocol you actually have. When that continuity breaks, the usual cost is a substantial amendment after first-patient-in—or a briefing document that contradicts the protocol.
Multi-Model AI Access
Consent readability, estimand algebra, and pre-IND question lists do not peak on the same model. This agent can shift among OpenAI, Anthropic, Google, xAI, DeepSeek, Qwen, and more—using one model for plain-language eConsent and another for multiplicity, alpha-spending, or Bayesian simulation notes—without juggling separate ChatGPT, Claude, or Gemini accounts. Single-vendor lock-in forces protocol prose, statistical framing, and regulatory strategy through one house style; confirmatory trial work does not.
Intelligent Tool Integration for End-to-End Workflows
Clinical Research Advisor runs a production path, not a chat window: indication, phase, and jurisdiction in; ranked design, estimand, and pathway out; then protocol, SAP, and consent critique; then schedule of assessments, monitoring, and SAE architecture; then pre-IND questions, CTIS structure, ClinicalTrials.gov timing, or CONSORT reporting. Google Scholar and Google Search ground endpoint and historical-control precedent; Google Drive and Dropbox keep the live protocol in the same thread; Notion can hold open decisions so the next iteration does not restart from a blank prompt.
Quality-by-design judgment rather than a fashionable template
ICH E6(R3) rewards protocols that name critical-to-quality factors and stay operationally feasible. The advisor will recommend a simple parallel RCT when that is stronger science than an under-specified adaptive or decentralized scheme, and it will say so when a rare-disease program cannot use a textbook Phase 3 sample-size target because most of those conditions affect fewer than 150 patients.
Principal investigators preparing a first registration trial
Academic PIs can pressure-test PFS versus OS, composite endpoints, diversity action plans, and PRO strategy before a Type B meeting, and leave with a documented estimand and pre-IND question list instead of waiting on a consulting cycle.
Biotech sponsors choosing a US versus EU first-in-human path
Sponsors get side-by-side framing of pre-IND versus EMA scientific advice, what belongs in the protocol versus the Investigator's Brochure, and how CTIS multinational assessment changes timelines relative to a US-only IND.
Study coordinators handling amendments and safety clocks
Coordinators can check substantial-amendment logic, SAE versus SUSAR criteria, and causality documentation against the study already in memory, then escalate with local SOPs and the protocol still governing.
Biostatisticians locking an estimand before sample size
Statisticians can walk ICH E9(R1) components—population, variable, intercurrent events, summary measure—then stress-test power, dropout inflation, multiplicity, and MCID-based deltas before unblinding defines populations after the fact.
Regulatory affairs professionals mapping devices, RWE, and rare-disease pathways
Regulatory staff can separate must-have requirements from gold-plating, including PMA-class companion diagnostics, decentralized sample collection, orphan designations, and when RWE is only a supplement to randomization.
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Clinical Research Advisor is an AI trial methodologist for designing, reviewing, and reporting studies with human participants. Typical work includes choosing a design, critiquing protocol and SAP language, specifying estimands and endpoints, planning DSMB and safety reporting, and framing FDA or EMA strategy. It supports principal investigators, sponsors, coordinators, biostatisticians, and regulatory staff, and it does not file applications on their behalf.
Clinical Research Advisor keeps the locked estimand, eligibility list, jurisdiction, and amendment history in memory so later SAP, consent, and safety answers do not contradict the protocol—something ChatGPT and Claude sessions routinely lose. It can route protocol prose, statistical framing, and regulatory questions across OpenAI, Anthropic, Google, xAI, DeepSeek, Qwen, and more instead of one vendor. Connections to Google Scholar, Google Search, Google Drive, Dropbox, and Notion let a concept move through design, document review, and briefing questions in one workflow rather than a pile of disconnected chats.
Clinical Research Advisor works with Google Scholar, Google Search, Google Drive, Dropbox, Notion, Gmail, and other connected apps so design work stays attached to evidence and the live protocol. Scholar and Search support endpoint precedent and historical-control checks; Drive and Dropbox hold protocol sections, SAP outlines, and consent drafts in the same thread; Notion can track open decisions such as primary endpoint or comparator. The chain is study concept to ranked design to document critique to operational and regulatory next steps.
Clinical Research Advisor can draft and review protocol sections, SAP outlines, consent language, DSMB charter structure, and briefing-document questions, but it does not submit an IND, CTA, or ethics package. Complete protocols are long, multi-author documents; the practical workflow is section-by-section review with your medical, stats, and regulatory team. Official filings still go through FDA ESG, CTIS, ethics committees, and qualified regulatory counsel.
Clinical Research Advisor is built to verify current FDA, EMA, and ICH positions when the answer depends on a date, fee, portal, or recently revised guideline, including E6(R3) quality-by-design and EU CTR/CTIS obligations. E6(R3) reached Step 4 on 6 January 2025 and comes into effect on 23 July 2025; the EU Clinical Trials Regulation became fully applicable on 31 January 2025, with CTIS as the application and oversight system. Treat the output as expert input to your team, then confirm binding requirements with regulatory affairs and the agency.
Yes. Clinical Research Advisor is built for programs that cannot use a textbook double-blind, placebo-controlled Phase 3 template and still need a design a regulator can defend. About 75 percent of rare-disease trials fail, and recruitment and retention—not the science—drive most of those failures; most rare diseases affect fewer than 150 patients. Externally controlled, adaptive, basket, and other non-standard options are discussed with the bias, power, and acceptance trade-offs made explicit.
Yes. Clinical Research Advisor runs with full feature parity on web, iOS, and Android, including speech-to-text, which matters when the question is whether an event meets SAE criteria, whether a change is a substantial amendment, and what the reporting clock is. The study context stays in memory so the indication and protocol logic are not re-explained at every clinic block. Local SOPs and the protocol still govern; the AI gives procedural clarity to act on, then escalate. iOS: Jenova on the App Store. Android: Jenova on Google Play.
No. Clinical Research Advisor does not replace a CRO, medical writer, or biostatistician. It is methodologist-level counsel for design decisions, protocol critique, and pathway framing that those teams still have to author, monitor, and sign. Use it to arrive at a coherent estimand, eligibility list, and reviewer question set before a consulting cycle or a substantial amendment exposes the contradiction.
No. Clinical Research Advisor will recommend a parallel-group randomized trial when that is the honest confirmatory design, and it will say when a fashionable adaptive, platform, or decentralized scheme trades bias, power, or operational feasibility you cannot defend. Remote visits, local labs, and digital endpoints are treated as fit-for-purpose questions, not as upgrades.
No. Protocol language, Investigator's Brochures, SAP outlines, and related study materials shared with Clinical Research Advisor are not used to train public AI models, are encrypted in transit and at rest, and are not sold or shared with advertisers. That matters for pre-IND packages and unpublished endpoints. Binding confidentiality still sits with your contracts, institutional policies, and regulatory counsel.
Bring the indication, intervention, phase, population, and jurisdiction, plus what is already locked—comparator, primary endpoint, sample size—and what is still open. Operational detail such as visit burden, competing trials, and rare-disease prevalence sharpens the design recommendation. A stuck decision is enough to start; a full protocol is not required.
Yes. Clinical Research Advisor walks through ICH E9(R1) components—population, variable, intercurrent events, and summary measure—before a sample-size calculation is treated as final. It stress-tests dropout inflation, multiplicity, interim alpha-spending, and what happens if the MCID is smaller than the hoped-for delta, and it keeps ITT, per-protocol, and safety populations from being defined after unblinding.
Clinical Research Advisor is part of Jenova, the most powerful AI agent platform in the world. Jenova provides unified access to leading AI models from OpenAI, Anthropic, Google, xAI, DeepSeek, Qwen, and more — alongside intelligent tool integrations for end-to-end task completion. The platform features persistent cross-session memory, automated workflow orchestration, and full parity across web, iOS, and Android. Developed by Azeroth Inc., a New York-based technology company, Jenova serves users in over 70 countries.
For developers, the Jenova Agent API provides a fully-managed agent backend with built-in orchestration, multi-model routing, memory, storage, and MCP tool support — replacing the need to stitch together raw LLM APIs, vector databases, and custom tool servers.
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