Update 1 — Project kickoff We are excited to share Pharma Saathi, an AI-powered Pharmacist Stand-In designed to provide clear, patient-friendly medication information while knowing when to involve a real pharmacist, doctor, or emergency service.
The idea started with one important question:
Can an AI assistant be helpful without pretending it knows everything?
Instead of building a generic medical chatbot, we are creating a bounded assistant based on pharmacist-approved knowledge and doctor-reviewed safety rules.
Our focus is on:
Clear medicine-information guidance.
English, Urdu, and Roman Urdu support.
Safe handling of unclear prescriptions.
Medicine storage, expiry, and missing-label guidance.
Side-effect and interaction screening.
Emergency escalation for red-flag symptoms.
Privacy-first design with no unnecessary patient data.
Update 2 — Safety-first behavior A major feature of Pharma Saathi is its escalation system.
The assistant does not guess medication doses, diagnose diseases, or recommend unapproved medicine substitutes.
For example:
text User: "My prescription dosage is not clear."
Pharma Saathi: ""The prescription is not clear. Do not guess. Please confirm with the pharmacist or doctor."" For emergency situations such as breathing difficulty, chest pain, severe allergic reaction, facial swelling, overdose, or unconsciousness, Pharma Saathi switches from regular counselling to a short, direct emergency response.
The goal is simple:
Answer when it is safe. Clarify when information is missing. Escalate when a real professional is needed.
Update 3 — Building the pharmacist knowledge base We have started converting pharmacist interview answers into a structured, source-linked knowledge base.
Each approved knowledge item includes:
json { "topic": "unclear_prescription", "risk_level": "high", "action": "escalate", "source_reference": "pharmacist_interview_part_3_q1", "approved_by": ["pharmacist", "doctor"] } This allows Pharma Saathi to retrieve relevant approved knowledge before answering instead of relying only on general AI output.
We are using a RAG-style approach so the knowledge can be reviewed, updated, and traced back to its source without retraining the entire model.
Update 4 — What we are testing next We are now testing Pharma Saathi against realistic medication-safety scenarios:
Unclear prescription instructions.
Unknown or unlabeled medicine.
Expired or damaged medicine.
Dose change requests.
Missed-dose questions.
Antibiotic early-stop questions.
Drug and herbal-product interaction questions.
Pregnancy and pediatric medication questions.
Emergency symptoms such as breathing difficulty or swelling.
Every output will be reviewed using three verdicts:
Agree — safe and correct.
Disagree — incorrect or unsafe.
Should have escalated — the system should have referred the user to a real professional.
Our goal is not to make an AI that answers every question. Our goal is to make one that responds responsibly.
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