Tareef Roustom
Principal, Pharmasight
Tareef Roustom is the principal of Pharmasight. He has spent his career building AI systems that run inside regulated pharmaceutical operations, for organisations including Johnson & Johnson, Boehringer Ingelheim, Gilead, Novo Nordisk, Sanofi and Chiesi.
His shipped work includes a clinical trial document processing and management platform integrated with Veeva Vault, where CDMO document dumps are classified into a sponsor eTMF through an architecture that lets eTMF owners change the taxonomy in real time without retraining a model; a marketing asset creation and management platform with MLR review built in; a dedicated MLR review orchestration and triage platform; and a life-science commercial marketing hub, which researches accounts, recommends products, and builds the commercial package and outreach strategy behind them.
He writes here about what actually happens between an AI pilot and a validated, inspected, production system — the part the vendor deck skips.
What the experience actually covers.
E-E-A-T is a search engine's phrase for something a pharma buyer works out in ten minutes anyway. Here is the version that survives that conversation, including the parts that are outside the remit.
- Regulatory frameworks worked in
- GCP, GMP, GVP and GLP; GAMP 5 Second Edition; EU GMP Annex 11 and the draft Annex 22; 21 CFR Part 11; ICH E6(R3), Q9(R1) and Q10; EU AI Act obligations as they land on regulated systems.
- Platforms integrated with
- Veeva Vault (Clinical, PromoMats, QualityDocs), eTMF and eCTD estates, eQMS and LIMS, CRM and marketing stacks, and the document repositories that sit behind all of them.
- Where the systems ran
- Johnson & Johnson, Boehringer Ingelheim, Gilead, Novo Nordisk, Sanofi and Chiesi — top-20 pharma through to mid-size biotech, in clinical operations, quality, regulatory and commercial.
- What is deliberately not claimed
- No published clinical outcomes, no peer-reviewed pharmacology, no legal or regulatory advice. Where an article states a regulatory position it names the instrument and the date, and where a claim cannot be sourced it says so.
How the writing here is made.
Regulatory guidance moves. An article that does not say when it was right is a liability in this industry, so every one of them does.
- 01
Every regulatory claim names its instrument
Not "the regulator requires" but which annex, which clause, which guidance, and whether the text is binding, draft or expected. The distinction between a binding 2011 Annex 11 and a draft revision under consultation is exactly the kind of thing a QA director tests a consultant on.
- 02
Every article carries the date its position was current
Shown in the document control strip at the top of the page and in the margin. When a guidance finalises, the article is revised and the revision date changes — it is not quietly edited.
- 03
Numbers are sourced or they are not used
Widely-quoted industry statistics are often circular citations back to a single unsourced slide. Where that is true, the article says so instead of repeating the number.
- 04
Nothing here is generated and published unread
AI is used in the research and drafting, as it is in the client work. The judgement, the sourcing and the position are the author’s, and the author is named on every page.
Latest from Pharmasight.
- 01Forecasting Software Fits the Curve. The Error Is in the Assumptions.Most pharma forecast error sits in entry dates, payer decisions and net price; machine learning helps with dense prescription data.
- 02Synthetic Control Arms at FDA: Agreed in Principle, Untested at ReviewFDA agreed in 2020 to consider Medicenna's hybrid synthetic control arm; six years on, the trial still awaits a partner.
- 03The Formulary Decision Your Claims Data Cannot SeeHealth systems run their own formularies; claims data shows the effect late and partially; vendor case studies seldom prove cause.
- 04What Clinical Trial Tokenization Links, What It Misses and What It CostsTrial tokenisation links consenting participants to claims through hashed identifiers; two published tokenised linkages reached under half of enrolled participants.
- 05Case study: Gedeon Richter's Regulatory Intelligence Triage, and What Four Clicks MeasureGedeon Richter automated regulatory alert triage with Clarivate; the only number is four clicks, and the binding clocks sit elsewhere.
- 06Case study: Keeping the MLR Queue Moving, From Triage to Review Built Into CreationWe built MLR triage and orchestration for pharma review queues, and a marketing asset platform with MLR review built in.
- 07Case study: Account Intelligence for a Supplier That Sells Into PharmaWe built a hub that researches pharma accounts, recommends products, plans outreach and tracks results, ranked by the supplier's strategy.
- 08Case study: What Launch Intelligence Found Behind a GI Diagnostic DelayWithin3 says pooled advisory boards, congress monitoring and field insights exposed a diagnostic delay. Its page reports outcomes without numbers.