Astra MD

Modern clinicians work under conditions of cognitive overload and informational fragmentation. Astra addresses three critical tasks that arise in nearly every clinical encounter: 1 Evidence retrieval: What do landmark randomized trials, guidelines, or systematic reviews recommend for a given scenario? 2 Diagnostic reasoning: How should competing diagnoses be weighted and investigated? 3 Therapeutic planning and documentation: What is the next best step, and how should it be communicated clearly and defensibly? Astra is designed to assist—not replace—clinical judgment. It surfaces cited, contextualized insights to inform decision-making without disrupting workflow. Functional Overview Research Agent
 Designed for time-sensitive decision-making, the Research Agent interprets focused clinical questions and retrieves concise, citation-backed summaries. It prioritizes high-quality evidence—such as randomized trials, meta-analyses, and guideline statements—and displays only results that can be traced to trusted, peer-reviewed sources. Differential Agent
 Given a presenting problem, the Differential Agent produces a structured, ranked list of possible diagnoses. Each entry includes supporting clinical features, relevant likelihood ratios, and recommended tests to refine pre-test probabilities. Its output is modeled after real-world diagnostic reasoning: probabilistic, prioritized, and evidence-aware. Whenever possible, it references landmark studies, scoring systems, or validated diagnostic criteria (e.g., Wells, Centor, PERC). Assessment & Plan Agent 
The A&P Agent transforms raw clinical impressions into structured documentation that mirrors modern standards of care. It frames problems in a SOAP-style format or by active issue, and recommends evidence-aligned management steps—labs, imaging, consults, pharmacotherapy, and monitoring. Each suggestion is mapped to a specific citation when available, creating a transparent, reviewable clinical trail. It is designed to support day-to-day rounding, rapid note writing, and preparation for case presentations or handoffs. Technical Foundations • Modular agent system: Each clinical function is handled by a distinct reasoning module trained and retrieved against relevant medical literature • Retrieval-based synthesis: Embedding-based search across a curated corpus of clinical trials and guidelines informs every response • Citation enforcement: Outputs are constrained to include traceable references (PMID, DOI); uncited claims are suppressed • Bayesian framework: Prevalence estimates and likelihood ratios are incorporated to estimate post-test diagnostic probabilities • Secure infrastructure: Data storage, access, and audit are managed according to modern clinical and security standards Scope and Limitations • Astra does not model institution-specific formularies or rare adverse effects. Clinicians should independently verify high-risk or off-label orders. • Literature indexing occurs on a scheduled basis; very recent preprints may not appear immediately. • Astra is intended as a decision-support tool and should not supersede clinical guidelines, supervision, or hospital policy. Roadmap (In Progress) • One-click EHR export for documentation and order templates • Drug–drug interaction modeling integrated into Plan generation • Personalized feedback loops based on anonymized usage patterns • Expanded specialty-specific guideline and trial coverage Our Commitment Astra is built on the principle that clinical reasoning is teachable, scalable, and improvable.
We aim to support physicians with tools that are rigorous, transparent, and aligned with modern standards of evidence-based medicine.