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Resources

Reading, listening, and watching from the pharma practice.

Real launches, real platforms, real numbers. Case studies, free books, webinar recordings, and the blog.

Track record

The launches behind the reading list.

Which pharma launches has DataKitchen worked on?

Karuna Therapeutics for the Cobenfy launch, Celgene for Otezla and Revlimid, and Acceleron. BMS acquired Karuna for $14 billion and Celgene for $74 billion. Merck acquired Acceleron for $11 billion. The platform stayed with the customer through every one of those transactions.

What results can you point to?

An average of 1.5 engineers built the whole Cobenfy launch platform at Karuna over two years, covering 50 integrated datasets. At Celgene, seven of our engineers supported $10 billion in US brand sales, and only 18 percent of engineering time went to data loading rather than new analyst work. One pharma cut data costs by 58% when we replaced its setup.

What error rate should we expect?

Low enough that the field stops asking. A commercial insights leader at Celgene reduced errors to about one per quarter and held that for years. The Otezla launch team shipped hundreds of schema and dataset changes a week with negligible error rates, because tests run at every stage rather than at the end.

Does this hold up in acquisition due diligence?

It has, three times. Due diligence scrutinizes whether the commercial story is accurate, auditable, and defensible, and a reconciliation trail on every feed is what turns "trust me" into "here is the check that passed." Our customers' platforms survived every exit and stayed with the customer each time.

Where should I start reading?

Two posts cover the argument end to end. The $100 Billion Secret explains why pharma companies hand commercial data to a specialized outside team instead of a general IT queue. The cash-runway post works the numbers for a small pharma launching in 12 to 24 months.
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Want a deeper conversation?

The writing only tells part of the story. Half an hour with our team will get you specifics on your stack, your launch window, and what the first sprint would look like.