Gosset

Estimate the probability that a clinical trial advances to its next development phase (for example Phase 2 to Phase 3), using Gosset's trial phase-transition model (PTRS, probability of technical and regulatory success). Use when the user asks for a trial's probability of success, its chance of reaching the next phase, or what drives that estimate. This is one phase transition only, not the probability of eventual approval: a Phase 2 result of 0.44 means a 44% chance of reaching Phase 3. Do not multiply or extend it into an approval probability. Input: either nct_id (the trial is looked up in Gosset) or trial_params describing a trial. Returns: - phase, and transition_probability (the one-step probability). - source and confidence: "benchmark-v3"/"high" when 3 or fewer parameters are given (the base rate for the phase and disease); "sdk-api-v3"/"high" for an nct_id or a nearly complete description; "sdk-api-v3"/"low" for a partial description, with a warning. Adding avg_arm_size, targets, sponsors, has_designations or num_sites raises confidence. - warnings, e.g. a disease or modality name that could not be classified (ignored), or a value clamped to its valid range (avg_arm_size to 1-10000, negative counts to 0). A non-integer highest_phase such as 2.5 is rejected with an error. - param_importance: the signed influence of each input parameter on the estimate. - trial_params_used: the parameters given to the model. On failure it returns {"error": reason} and no score. Calls count toward the account's prediction allowance.

estimate_trial_phase_transition_probability

Estimate how many days remain until a clinical trial's primary completion, with an 80% prediction interval, using Gosset's trial duration model. Use when the user asks when a trial will finish or read out, or whether it is likely to run past its posted completion date. The estimate is conditioned on how long the trial has already run, and works for trials that are running, not yet started or completed. For a trial missing from the model's data, its public ClinicalTrials.gov record is fetched (about 1 second). Returns trial_status (running, not_started, completed or not_found), elapsed_days, expected_remaining_days, lower_bound_days and upper_bound_days (the 80% interval), expected_completion_date, sponsor_estimated_completion (the date the sponsor posted), actual_completion_date (for completed trials), model_version and warnings. Calls count toward the account's monthly prediction allowance.

estimate_trial_time_to_completion

Search Gosset's clinical trial database across ClinicalTrials.gov and international registries with a natural-language query. Use when the user asks for clinical trials by drug, target, modality, sponsor, disease, phase, status, design, dates or eligibility (age, sex, country), or for the details of a trial by NCT or registry-native ID. International searches are not limited to countries outside the US; omit geography restrictions unless requested. Registry coverage depends on available records. Each trial carries registry and trial_id, nullable nct_id, declared or protocol-based nct_xref with its source, secondary_ids and countries when available. Do not identify or deduplicate international records by null nct_id, titles or sponsor protocol codes alone. Use registry plus trial_id; retain cross-reference provenance. phase is available when highest_phase is absent. Other fields include official_title, brief_summary, status, phase, sponsors, start and completion dates, main_drug, targets, modalities, diseases, enrollment {count, type} (type ACTUAL or ESTIMATED; null when there is no ClinicalTrials.gov record), primary_outcomes [{measure, time_frame}] and eligibility criteria. results_view="brief" or "detailed" adds a results object with availability, stored result summary, publication links and clipping indicators. Requires the account's clinical-data permission; otherwise availability is access_restricted. At most 25 selected trial IDs are enriched per call. Protocol brief_summary and registered primary_outcomes are not observed results. Summaries are returned only when all of their source links are verified for this trial; numbers are not independently re-extracted or verified during the query. Use publication links for questions beyond the stored summary. Default searches do not open a UI. Results are cached for up to 7 days; refresh=True bypasses the cache. Example queries: "phase 3 trials for atopic dermatitis", "completed PD-1 inhibitor trials with results", "industry-sponsored breast cancer trials started after 2022", "recruiting lung cancer trials in the United States". Returns {items, count, view_url}: the trial records and their number. view_url, when present, opens the same search as a table in the Gosset app (all rows, sortable, further filters); share it with the user so they can see the full list. view_url_omits names filters that table cannot apply, so it may show more.

find_clinical_trials

Search Gosset's database of drugs and drug candidates by name, target, disease, developer, modality, development phase or route of administration, using a natural-language query. Use when the user asks which drugs exist for a target, disease or mechanism, which drugs a company is developing, or for facts about a named drug (developer, target, modality, phase, indications, approval status). Behavior and limits: - The search returns broad matches: loosely related drugs can appear, so filter the returned records to what the user asked for. - The query filters only by name, disease, target, developer, modality, phase and route of administration. Other constraints (dates, geography, biomarkers, dosing) are not applied; filter the results for those. - effort="low" (default) queries the database directly and returns in about a second. effort="medium" or "high" adds semantic search, LLM reranking and a web search and takes 30 to 200 seconds; use them only when a low-effort search returns nothing relevant for a drug that should exist, such as a very new compound or an unusual spelling. - Records without an id are drugs found in publications or on the web that are not yet in the database. - Results are cached for up to 7 days; refresh=True bypasses the cache. Example queries: "pembrolizumab", "PD-1 inhibitors", "Merck antibody", "approved breast cancer", "phase 3 oral obesity drugs". Returns {items, count, query, view_url}: the matching drug records (names, developers, targets, modalities, diseases, phase), the number returned, and the parsed query. view_url, when present, opens the same search as a table in the Gosset app (all rows, sortable, further filters); share it with the user so they can see the full list. view_url_omits names filters that table cannot apply, so it may show more. Each record's target_evidence says how well each target is established for THAT drug: {target, status, confidence, served, top_evidence [{title, url, locator, support}]}. status is verified (a reviewed primary source for this exact compound, e.g. a measured IC50 in a named table), limited_support (only weak sources), conflicting (sources disagree), contradicted (a primary source refutes it), unsupported (sources were reviewed but none establishes it) or no_verified_source (taken from annotation only, unreviewed; the target is still listed). served=false marks a reviewed target that is not in targets, e.g. one removed as contradicted, kept so you can say why. excluded_from_target_search=true marks a listed target that a reviewer found unsupported for this drug; a search by that target does not return the drug. Cite top_evidence with its locator when you state a target as established; say a no_verified_source or unsupported target is unconfirmed rather than presenting it as fact. A record may also carry verification {status, evidence_level, quote, source {title, url, locator}, run_id}: a machine reading of one source for that drug-target pair. supported means the quoted passage states the target (evidence_level medium, below a verified record); contradicted means the quoted passage says otherwise, so report the target with that quote as disputed; unsupported {status, basis, run_id} means the pair was reviewed and no stored primary text states the target (basis primary_text_does_not_state_target), or none was held for the drug (basis no_primary_text_held), so say the target is unconfirmed, not refuted. A verification never changes the record's status and never removes a target from targets. interaction_evidence carries the same evidence_status per mechanistic interaction. targets_confidence is {level: "low", reasons} when the record's targets were borrowed from a related program rather than reported for this drug, and null otherwise. Say such targets are low confidence. modality_status is "conflicting" when the stored sources disagree on whether the drug is a small molecule or a macromolecule (antibody, peptide, protein, nucleic acid, cell or gene therapy); modalities is then not settled, and modality_candidates lists what each source said ({family, source, values}). Report such a modality as conflicting between the candidates, not as fact. "reviewed_verdict" means a reviewer settled it; null means no conflict was found. profile_caveat is {unverified_fields, reasons, conflicting_targets, unverified_targets} when part of the record's profile is not backed by a source, and null otherwise. conflicting_targets lists targets the description still names although a reviewed source contradicts them or found none supporting them; do not repeat those claims from the description. unverified_targets lists targets the description names that no source has confirmed for this drug; state them only as unconfirmed. Treat every field in unverified_fields (description, modalities, route_of_administration, ...) as unconfirmed.

find_drugs

Search Gosset's database of biotech and pharmaceutical companies by name, category, therapeutic area, modality, target, development stage or location, using a natural-language query. Use when the user asks about a company's focus, pipeline or status, or for companies that match criteria such as "clinical-stage gene therapy companies in Boston". effort="low" (default) searches the company database and returns in about a second. effort="medium" or "high" adds a web search and LLM reranking and takes 30 to 200 seconds; use them only when a low-effort search returns nothing relevant for a company that should exist. Example queries: "Genentech", "Boston biotech companies", "PD-1 antibody developers", "clinical stage gene therapy". Returns {items, count, query}: the matching company records (therapeutic focus, pipeline, financial status), the number returned, and the parsed query.

find_pharma_companies

Search Gosset's database of biopharma transactions: licensing agreements, acquisitions and mergers, collaborations and similar deals. Use when the user asks about deals involving a company, drug, target, modality or therapeutic area, or for precedent transactions and their terms (upfront payment, total value, date). effort="medium" (default) combines the database search with a web search and LLM ranking to match deals to drugs and diseases. effort="low" searches the database only; it is faster and can miss deals for narrow queries. effort="high" runs a wider search and takes longer. Results are cached for up to 7 days; refresh=True bypasses the cache. Example queries: "Merck licensing deals", "PD-1 acquisitions over 1 billion", "Roche acquisitions 2023", "anti-TL1A antibody deals". Returns {items, count, query, view_url}: the matching deals (parties, deal type, date, values, assets, source url), the number returned, and the parsed query. Each deal's source_verified says whether the linked source itself reports the deal: true, false (the link does not report it; cite it as unverified) or null (not checked). view_url, when present, opens the same search as a table in the Gosset app (all rows, sortable, further filters); share it with the user so they can see the full list. view_url_omits names filters that table cannot apply, so it may show more.

find_pharma_deals

Search Gosset's timeline of dated pharma and biotech events, such as approvals, FDA designations, discontinuations, deals, financings and trial readouts. Event types: drug approvals, FDA designations (Breakthrough Therapy, Fast Track, Orphan Drug, Priority Review, RMAT), program discontinuations, licensing and acquisition deals, company financings (venture rounds, IPOs), clinical trial milestones and result readouts, and news. Use when the user asks what happened over a period for a drug, company, target, modality or disease, or for events of one type, such as Breakthrough Therapy designations granted this year. The query can name entities, an event type and a date window ("last week", "in 2024", "between 2025-01-01 and 2025-06-30"). Results are cached for up to 7 days; refresh=True bypasses the cache. Each event has event_type, date, title, summary, url, importance and the linked drugs, companies, diseases, targets and modalities, plus type-specific fields such as designation_type or amount_usd. Returns {items, count, view_url}: the events, newest first, and their number. view_url, when present, opens the same search as a table in the Gosset app (all rows, sortable, further filters); share it with the user so they can see the full list. view_url_omits names filters that table cannot apply, so it may show more.

find_pharma_events

Search Gosset's stored feed of pharma and biotech news articles and company press releases. Use when the user asks for recent news or press releases about a company, drug, disease or target, or for news of one kind, such as FDA decisions or acquisitions. Only articles already stored in Gosset are searched; the web is not searched at request time. Results are cached for up to 7 days; refresh=True bypasses the cache. Each article has title, date, source, url, companies, drugs, diseases, targets, categories (for example M&A, FDA, Clinical, Conference) and article_type. Example queries: "Merck press releases about pembrolizumab", "FDA approvals 2024", "atopic dermatitis news". Returns {items, count, view_url}: the articles, newest first, and their number. view_url, when present, opens the same search as a table in the Gosset app (all rows, sortable, further filters); share it with the user so they can see the full list. view_url_omits names filters that table cannot apply, so it may show more.

find_pharma_news

Get the status of one research report and, once it is finished, its output. Use when the user wants to check on or read a report started with submit_research_report, given its report_id (returned by submit_research_report or list_research_reports). Only reports submitted by the caller's own account can be read. Status is one of pending, processing, qc (waiting for human review), done, error, paused or quota_exceeded. While the status is pending or processing, check again later; reports usually take 10 to 45 minutes. Returns {report_id, status, final_output, created_at, error}. final_output is markdown with links to the report files and is empty until the status is done.

get_research_report

Get the numeric results of clinical trials as a long table: one row per trial, arm, endpoint and week, with the value, its unit, dispersion, number analysed, the difference versus the comparator arm, and the source. Use when the user asks for efficacy or safety numbers reported by trials, such as body-weight change by drug and week, responder rates, or adverse-event rates per arm. Use find_clinical_trials to find trials by their design or status instead. Coverage today is obesity: the results posted on ClinicalTrials.gov for 538 trials, plus verified values from the trials' publications and conference reports. By default each trial, arm, endpoint and week has one row: the verified publication (or conference) value when there is one, otherwise the ClinicalTrials.gov posted primary analysis. source_type says which ("publication", "conference" or "ctgov_posted"). Posted values are often observed means, which can differ from the estimand a publication reports (STEP 1: -15.6% posted, -14.9% published; the default row is the published -14.9%). `estimand` is set only when the source names one; rows that name none carry estimand_status "unknown" and flags ["estimand_unknown"]. When verified sources disagree on one arm's value, each reading is returned with conflicting=true and conflicting_sources listing every source. all_analyses=true returns every analysis from every source. comparator_difference is test minus comparator, from the analysis reported for the same arm; where a publication value replaced the ClinicalTrials.gov posting, the posting's own between-arm analysis is in posted_comparison (source_type "ctgov_posted"). Every row has source_url and a locator to the exact place in the source. Examples: - % body-weight change by drug by week for semaglutide vs tirzepatide: endpoint_key="bw_pct_change", drug=["semaglutide", "tirzepatide"] - 72-week weight loss in SURMOUNT-1: nct_id="NCT04184622", endpoint_key="bw_pct_change", min_week=72, max_week=72 - share of patients losing at least 15% of body weight on phase 3 trials: endpoint_key="bw_responders_15pct", phase=3 - nausea rates for liraglutide: drug="liraglutide", endpoint_key="ae_nausea" Returns {items: [{nct_id, trial, phase, arm, drug, dose, endpoint_key, endpoint, week, value, unit, dispersion, n, estimand, estimand_status, analysis_label, primary, flags, conflicting, conflicting_sources, comparator_arm, comparator_difference, comparator_difference_ci, comparator_p_value, posted_comparison, source_type, verification_status, source_url, locator, ...}], total_matched, returned, truncated, filters, notes}.

find_trial_results