AI Clinical Trial Matching Software

AI clinical trial matching is software that automates the difficult work of comparing patients against clinical trial eligibility criteria to find likely matches. The challenge is real on both sides. Trial eligibility criteria are complex, written in dense clinical language, and often numerous, while patient data is scattered across structured fields and unstructured notes in the EHR, and increasingly includes genomic data for biomarker-driven trials. AI helps by using natural language processing to parse eligibility criteria into structured logic, extracting relevant patient data including facts buried in notes, and applying a matching engine that identifies and ranks candidate trials for each patient, or candidate patients for each trial. Crucially, the software pre-screens and surfaces candidates; research coordinators and clinicians confirm eligibility and make enrollment decisions, because trial eligibility has strict requirements and real consequences. Because matching draws on genomic and clinical data, it connects to precision medicine platforms. Done well, it dramatically reduces screening effort and helps more eligible patients find trials, without removing human judgment from enrollment.

Taction Software delivers trial matching as a full engagement shaped to your setting, whether you are a cancer center, an academic medical center, a research site, a sponsor or CRO, or a trial-matching company. We map your trials, patient data sources, and coordinator workflows first, then build the modules that fit: eligibility parsing, patient data extraction including notes, the matching and ranking engine, trial registry integration, coordinator review workflows, and reporting. Because matching depends on data from the record and often genomics, we integrate accordingly and draw on our data practice. We design the software to pre-screen and prioritize, presenting candidates with the evidence behind each match so coordinators can verify quickly. We validate matching quality and monitor the models, aligned with our healthcare AI observability practice, watching accuracy and fairness in who gets surfaced. Every module is composable, so you can start with matching for a set of trials and expand over time. The goal is faster, broader trial matching that reduces manual screening while keeping eligibility and enrollment decisions with people.

A purpose-built trial matching platform delivers value that manual screening cannot, because matching is high-effort, high-complexity, and easy to miss. The clearest benefit is faster, more complete enrollment: surfacing likely-eligible candidates quickly helps trials enroll, which is often their biggest bottleneck, and helps eligible patients find trials they would otherwise miss. Reducing manual screening frees coordinators from combing through charts against long criteria lists, letting them focus on confirming matches and enrolling. Genomic-aware matching supports the biomarker-driven trials central to modern oncology. Ranking and match evidence let coordinators verify candidates efficiently rather than starting from scratch. For patients, broader matching can expand access to potentially beneficial trials, which raises an equity dimension the software should support fairly. For sponsors and sites, faster enrollment shortens timelines and cost. Because the software keeps humans in charge of eligibility, it captures these benefits without the risk of automated enrollment errors. Over time, it becomes a durable enrollment capability rather than a one-off tool.

Taction Software follows a compliance-first, validation-focused process suited to clinical AI. We begin with discovery, documenting your trials, eligibility complexity, patient data sources, and coordinator workflows. We then design the architecture: eligibility parsing, data extraction, the matching engine, registry integration, and review workflows, with human confirmation built into the flow. Development runs in iterative sprints with research and clinical review, so coordinators shape how candidates and match evidence are presented, which determines whether the tool is trusted and used. We validate matching quality carefully, measuring both how well it finds true matches and how well it avoids false ones, and we assess fairness in who gets surfaced. We build monitoring so model performance stays sound over time. We deploy with the oversight trial workflows require, then support tuning and expansion. Throughout, we design the software to assist coordinators, not replace their judgment, because eligibility determination and enrollment are consequential decisions that must remain human.

Trial matching processes sensitive clinical and genomic data and influences patient access to trials, so security, accuracy, and fairness are foundational. Taction Software builds on a HIPAA-aligned foundation, with encryption in transit and at rest, granular access controls, audit logging, and Business Associate Agreements where applicable, and we apply heightened protection to any genomic data. Our architecture supports healthcare-grade cloud deployment on AWS or Azure and standards-based interoperability using HL7 and FHIR, so the platform can access the patient data matching requires, including notes via NLP. We build eligibility parsing and matching for accuracy and transparency, presenting the evidence behind each match so coordinators can verify, and we validate matching quality rather than assuming it. Because matching can affect who is offered trials, we assess and monitor fairness, aligned with our healthcare AI observability practice. Above all, the platform surfaces and ranks candidates; coordinators and clinicians confirm eligibility and make enrollment decisions.

Taction Software is a US-based healthcare software company founded in 2013, with offices in Chicago, Cheyenne, Austin, and Sacramento. We build healthcare software exclusively, so clinical data, NLP, and compliance are part of our default process rather than afterthoughts. We have delivered more than 200 healthcare projects, including EHR and EMR platforms such as Voyant Health, FDA-registered mobile applications, and behavioral health tools. That data and AI depth matters in trial matching, where parsing complex criteria and extracting scattered patient data accurately is the core challenge. We work as a candid partner, building matching that assists coordinators with transparent, validated results rather than opaque automation. Our leadership brings deep, hands-on expertise, with our CEO contributing more than 20 years of personal experience in software and healthcare technology. Building with Taction means partnering with a team that has repeatedly taken healthcare software from concept to production in regulated settings.

Trial matching pricing depends on scope, eligibility and data complexity, and integrations. Taction Software scopes each engagement to your setting, and typical ranges are as follows. A focused module or MVP, such as matching for a defined set of trials with review workflows, generally falls between $40,000 and $80,000. A full trial matching platform with eligibility parsing, note extraction, ranking, registry integration, and monitoring typically ranges from $80,000 to $200,000. Enterprise platforms across many trials, deep EHR and genomic integration, and advanced NLP start at $200,000 and up. Final pricing follows a discovery phase that defines trials, data sources, and workflows. We provide clear, itemized estimates so you can validate matching value on a focused set of trials and expand.