Algorithms stop at the flag. Your obligation doesn't.
AI-PV platforms now detect, score, and draft competently. But a flag is not a decision. The regulatory obligation runs further: a qualified physician must adjudicate benefit-risk, and the review must leave a documented trail — who reviewed, when, under what criteria, with what outcome. The gap stays invisible until the worst possible moments:
- ▶ The first SAE wave after enrollment opens
- ▶ Partner or investor diligence on your safety setup
- ▶ A PSUR cycle with an undersized team
- ▶ The inspection that asks the question below
"Show me the documented physician review for these fourteen AI-flagged signals."
The inspection question every AI-assisted safety program must answer — with a name, credentials, and an audit trail.
The economics are not complicated
Inadequate-oversight findings trigger remediation programs, clinical holds, and approval delays measured in months.
Against clinical assets often valued in the hundreds of millions, months of delay dwarf any oversight budget.
Partners and investors now probe AI governance; a missing oversight trail reprices a deal — or kills it.
Independent, documented physician oversight is among the least expensive insurance a clinical-stage company can buy.
And unlike insurance, it also makes the program faster: narratives in minutes instead of hours, signals adjudicated as they emerge, diligence questions answered from a system of record instead of a scramble.
Four ways in — one standard of judgment
Readiness Assessment
Fixed-fee, 3–4 week diagnostic of your safety governance, systems, and AI exposure — with a graded gap analysis and remediation roadmap you own outright.
Signal Definition & Pre-IND
Clinically rigorous signal criteria for your program — CRS, ICANS, DLTs — mapped to data elements, ready for regulator alignment.
Continuous Medical Oversight
A named, credentialed oncologist as your documented safety reviewer — adjudication, expedited sign-off, SRC/DSMB support, every decision audit-ready.
Inspection & Governance Readiness
Mock-inspection review of your AI oversight documentation and SOPs — so the inspection question has an answer before it is asked.
From flag to defensible decision in five steps
Signal arrives
AI-flagged event lands in the review queue with full source data.
➤AI assembles
Draft narrative and suggested grade in seconds — labeled suggested.
➤Physician decides
Named reviewer adjudicates — can override, documents rationale.
➤Sign-off binds
Part 11-style e-signature: identity, time, and meaning locked in.
➤Trail exists
Tamper-evident audit record, generated as the work happens.
The architectural invariant: no AI output becomes a record of decision without a physician's review and signature. We built the bypass out — because the regulatory obligation is human.
Where does your program sit today?
No documented process, no designated owner, no records produced.
Work happens, but person-dependent — records reconstructable only after the fact.
Documented, owned process; records exist but lag, scatter, or need assembly.
Self-evidencing: attributable, timestamped records, retrievable on demand.
The test behind the scale: when an inspector asks for the documented review, Level 2 means reconstruction — and reconstruction shows gaps. Level 4 means the answer is produced in the meeting. Our Readiness Assessment grades all five safety domains on this scale — and hands you the roadmap from where you are to Level 4.
Grade yourself in 2 minutes.
Ten questions across the five domains, an instant graded result, and your two biggest exposures named — no call required.
The toxicity is modality-specific. So is the judgment.
Advanced therapeutics fail when their toxicity is treated like chemotherapy. Our oversight is grounded in the clinical reality of each modality.
CAR-T — CRS & ICANS
The assumption baked into legacy pharmacovigilance fails CAR-T patients. Oversight must anticipate the acute, time-critical toxicity window — not react to it in batches.
Antibody-Drug Conjugates
ADCs are not chemotherapy. Treating their organ-specific toxicity like chemotherapy is a clinical safety error — it demands targeted, organ-aware monitoring.
Radioligand Therapy
RLT carries a dosimetry-safety gap that conventional PV is not trained to see — marrow reserve, renal function, and cumulative dose all in view.
AMOIP — Acute Multi-Organ Instability Phase
The clinical window conventional pharmacovigilance wasn't designed to see — our framework for the acute, high-acuity period where advanced-therapy safety is won or lost.
Read the full clinical briefings from Dr. Ashok Srivastava →
Named principals. Backed by depth.
IHASG is delivered by the founders directly — not staffed down. The judgment stays with named experts at every step.
Dr. Ashok Srivastava, MD, Ph.D., MBA
Named Physician Reviewer
Board-certified oncologist. 130+ oncology & hematology trials across 20 countries. 27 INDs, 9 NDAs, 3 BLAs. Lead physician on the AUCATZYL® CAR-T BLA. Harvard Dana-Farber / NCI trained.
Elias Tharakan
Platform & AI Governance Architect
Architect of the industry's first unified eClinical SaaS platform. 1,000+ clinical trials powered. 20 years building compliant AI and data-integrity frameworks for regulated clinical environments.
Backed by a wider expert network
Beyond the founding principals, AyurDatta works with a curated network of oncology KOLs, principal investigators, and safety specialists — available to support signal consultation, SRC/DSMB participation, and modality-specific review.
IHASG runs on the Medical Oversight Workbench.
The tooling that makes physician judgment fast enough for signal speed — and documented by default. Live demo: eight minutes, a case like yours, end to end.
Explore the Workbench →Let's make sure you have the answer first.
Start with the Readiness Assessment: 3–4 weeks, fixed fee, a graded roadmap you own — scoped on one call.
Book a Readiness Assessment