Maven Bio offers a wide range of filters that help you scope companies, drugs, trials, indications, mechanisms, targets, and document lists with precision. Filters can be combined to build clean lists and structured smart tables tailored to specific research needs.
Pro Tips for Effective Filtering
Use multiple filters together to scope more refined lists; filters follow AND/OR logic, meaning items included must and will satisfy all applied conditions.
Adjust filters anytime from the Applied Filters panel.
Use the “suggest filters” window to scope the precise list of items you wish to include in your analysis.
If you’re not able to find an exact filter for what you’re looking for, first narrow the list as much as possible using the available (or suggested) filters. Then, apply AI columns to further weed out entities that don’t meet your criteria.
When supported by the data, AI columns becomes filterable and can help create new list dimensions.
Combine scientific, regulatory, clinical, financial, and company-level filters for the cleanest lists and get ready to enrich them using AI Columns.
Drug Filters
Drug filters help you scope and create lists of assets by their development context, modality, mechanistic profile, clinical characteristics, company involvement, etc.
You can begin by narrowing drug lists using development attributes such as global status, sub-global status, USA status, and sub-USA status.
Additional drug attributes like active/inactive state, biologic class, biosimilar status, fixed combination, or inclusion in a research program help you refine drug lists further.
Product Type filters classify a drug by its therapeutic modalities—for example small molecule, antibody/peptide, gene therapy, cell therapy, radiopharmaceutical, vaccines, etc.—and their various sub-types, allowing you to generate modality-specific drug lists.
Regulatory designation filters (Orphan Drug, Fast Track, Breakthrough Therapy, PRIME, RMAT, QIDP) make it easy to surface lists of programs with special pathways or accelerated-development potential.
Clinical refinements such as patient populations, PK/PD profile, adverse events, and route of administration can be used to scope drug lists based on how a drug is used or studied. Mechanistic filters (MOA, targets, drug classes) and disease-level filters (indications, therapeutic areas, indication phases) help anchor drug lists in scientific and clinical space.
Company filters let you scope drug lists by primary company or all companies involved. The primary-company market-cap filter adds a business lens—useful for BD, strategy, or investment analysis.
Trial Filters
Trial filters give you control to scope and generate trial lists by study design, scientific purpose, geography, population, interventions, and sponsor involvement.
You can filter trials by NCT ID, titles, study type, summary, trial focus, or therapeutic area. Development timing—trial status, start/completion dates, primary completion date, and posted date—helps contextualize where each trial sits in its lifecycle and supports precise trial list creation.
Population and eligibility details such as enrollment numbers, enrollment type, gender eligibility, acceptance of healthy volunteers, inclusion/exclusion criteria, and outcomes measured allow deeper refinement of trial lists.
Trials can also be scoped by countries involved, drugs studied, mechanisms and targets, drug class, indication, therapeutic area, sponsoring or collaborating companies.
Study design characteristics—including allocation method, intervention model, masking/blinding, objectives, hypotheses, intervention summaries, and overall design summaries—let you isolate and create lists of highly specific study designs.
Company Filters
Company filters combine identity, pipeline depth, and financial characteristics to help you scope and create lists of organizations at multiple levels.
Core identity details include the company’s name, website, LinkedIn URL, headquarters country, stock exchange, ticker symbol, founding year, operational status, corporate status, and employee count.
Pipeline-focused filters capture a company’s scientific footprint: total active programs; mechanisms, targets, drug classes, indications, and therapeutic areas associated with those programs; and the highest global, U.S., and sub-regional phases reached. These enable efficient construction of pipeline-based company lists.
Financial filters (for public companies) include market capitalization, annual revenue, net income, EBITDA, free cash flow—allowing you to segment and list companies by size, financial performance, and commercial maturity.
Indication Filters
Indication filters help you scope and organize lists of diseases. Indication lists can be refined by: name and description, associated drugs and companies, associated mechanisms and targets, therapeutic areas.
You can also filter by development maturity using highest global and U.S. phases, total program count, number of active programs, and active-program percentage—supporting phase-specific indication list creation.
Mechanism and Target Filters
Mechanism and target filters work the same way—each lets you scope and create lists of biological mechanisms or targets by showing names and descriptions, associated drugs and companies, linked indications and therapeutic areas, highest global and U.S. phases, total vs. active program counts, and the percentage of active programs. These filters are especially useful for target-based discovery and competitive analysis.
Document Filters
Documents can be refined and turned into structured document lists based on high-level metadata and associated entities. Filters include: document title and type (including but not limited to press releases, earnings transcripts, SEC filings, publications, corporate presentations, etc.), publication date, source URL, summary, associated companies and drugs.
This enables targeted retrieval and list-building across corporate, regulatory, scientific, or clinical documentation.