In Pharma value chain, PBMs manage to benefit

JIM GREENWOOD | April 8, 2019

article image
As 2020 Democratic presidential aspirants lean into their game of one-upsmanship on policies that would slow medical progress and undermine the U.S. biopharmaceutical industry, it’s a relief to see the Senate convene a hearing Tuesday on the self-dealing middlemen in the drug delivery system whose profits are largest when a drug’s list price is highest. Pharmacy benefit managers (PBM) help determine which medications get placed on insurance formularies and how much patients pay out of pocket for drugs they often can’t live without. However, PBMs are not primarily concerned with negotiating lower drug prices on behalf of patients, no matter what their press releases say. Their allegiance is to their shareholders and the health insurers who hire or own them. PBMs were originally conceived to help employers and insurers negotiate the best prices on prescription drugs, a fine idea in a market-based health care system like ours. But massive industry consolidation has fundamentally changed the way they do business. In private, PBMs ask biopharma companies to preserve high list prices and write them larger rebate checks in exchange for prime formulary placement. In public, these middlemen castigate drug companies for high prices while laughing all the way to the bank.


Affiliated Genetics, Inc.

After 23 years of operations providing DNA testing applications, genomic services, and DNA-based, human identity testing, Affiliated Genetics has closed.


Better Purification and Recovery in Bioprocessing

Article | August 2, 2021

In the downstream portion of any bioprocess, one must pick through the dross before one can seize the gold the biotherapeutic that the bioprocess was always meant to generate. Unfortunately, the dross is both voluminous and various. And the biotherapeutic gold, unlike real gold, is corruptible. That is, it can suffer structural damage and activity loss. When discarding the dross and collecting the gold, bioprocessors must be efficient and gentle. They must, to the extent possible, eliminate contaminants and organic debris while ensuring that biotherapeutics avoid aggregation-inducing stresses and retain their integrity during purification and recovery. Anything less compromises purity and reduces yield. To purify and recover biotherapeutics efficiently and gently, bioprocessors must avail themselves of the most appropriate tools and techniques. Here, we talk with several experts about which tools and techniques can help bioprocessors overcome persistent challenges. Some of these experts also touch on new approaches that can help bioprocessors address emerging challenges.

Read More

Making Predictions by Digitizing Bioprocessing

Article | April 20, 2021

With advances in data analytics and machine learning, the move from descriptive and diagnostic analytics to predictive and prescriptive analytics and controls—allowing us to better forecast and understand what will happen and thus optimize process outcomes—is not only feasible but inevitable, according to Bonnie Shum, principal engineer, pharma technical innovation, technology & manufacturing sciences and technology at Genentech. “Well-trained artificial intelligence systems can help drive better decision making and how data is analyzed from drug discovery to process development and to manufacturing processes,” she says. Those advances, though, only really matter when they improve the lives of patients. That’s exactly what Shum expects. “The convergence of digital transformation and operational/processing changes will be critical for the facilities of the future and meeting the needs of our patients,” she continues. “Digital solutions may one day provide fully automated bioprocessing, eliminating manual intervention and enabling us to anticipate potential process deviations to prevent process failures, leading to real-time release and thus faster access for patients.” To turn Bioprocessing 4.0 into a production line for precision healthcare, real-time release and quickly manufacturing personalized medicines will be critical. Adding digitization and advanced analytics wherever possible will drive those improvements. In fact, many of these improvements, especially moving from descriptive to predictive bioprocessing, depend on more digitization.

Read More