DIABETES BUSINESS NEWS:
Diabetes tech market still has a clear favorite was published by Jason Aycock for SeekingAlpha.com, 15 December 2021.
On the Continuous Glucose Monitoring, the market stayed strong this year, likely growing in the low- to mid-30% range by users, and just over 30% in dollar terms. While CGM’s type 1 diabetes penetration in the U.S. is closing in on 60%, “we see room to 80%-plus” in the next few years, and say investors shouldn’t underestimate growth tailwinds from lower penetration outside the U.S., accelerating IIT type-2 uptake in the US., and a “rapidly evolving focus on NIT T2/pre-diabetes/whole-person health.”
Meanwhile the insulin pump market rebounded this year (to about 6% growth by patient volume and 15% growth in dollar terms), and that’s set to continue; improved AID outcomes can help sustain solid growth, though DME and “hassle factor” limitations are likely to limit pump growth vs. CGM. A
Its top idea across the group is still DexCom, which looks to have its “best international competitive positioning in years.” Like Abbott, DexCom likely grew its CGM user base by 35-40% this year, the firm says. It rates the stock Outperform with a $625 price target.
The name it struggles with the most is Insulet. The company’s global Omnipod revenue is “growing nicely” above market, at an estimated 19%. But the company will keep ceding share across Europe next year to Tandem Diabetes Care, which was once again the fastest-growing company in the pump market (an estimated 39% global revenue growth this year). While that share loss is a concern, the firm thinks FDA O5 clearance in the first quarter – and a “clear/credible path” to launching O5 in Europe in the second half of next year – could be enough to boost sentiment and drive Insulet to outperform. But without both of those happening, it would reconsider its bullish rating amid structural European growth challenges. It has a $315 price target on Insulet, implying 23% upside.
For its part, Tandem should benefit from DexCom’s access wins in Germany, France and (potentially) the UK, but “with TNDM’s U.S. growth potentially slowing in 2022 even before competitive AID system launches build starting in 2H-22,” Baird is staying Neutral there.
As red flags multiplied, Johnson & Johnson kept quiet on popular diabetes drug was written by Chad Terhune and Robin Respaut, for Reuters.com in an expose called “Out of Control”, 8 December 2021. Invokana was the company’s big bet on the vast market for type 2 diabetes drugs. While sales soared, Reuters found, executives rebuffed their safety experts’ advice to warn regulators about a dangerous complication. (Makes me think, sadly, about the Oxycontin drug so heavily and irresponsibly promoted by Purdue Pharma and the Sackler family. How dare they hurt people so callously?!)
The drug, Invokana, had been on the market less than a year, and sales were already rocketing toward $1 billion. In separate and strikingly similar reports sent to the company and reviewed by Reuters, doctors from across the United States told of 18 patients sickened by a rare and potentially fatal buildup of acid in the blood, known as diabetic ketoacidosis, or DKA, within days or weeks of starting Invokana. Dr Bruce Leslie, who led the safety team at the March 2014 meeting, recommended that the company alert U.S. and European regulators. “I think we should get out in front of this,” Leslie told executives in the room, as he recounted in an interview with Reuters. “Otherwise, it could come back and bite us in the ass.”
The executives weren’t persuaded. They decided to take no action. By July 1 that year, J&J had learned of 39 cases of ketoacidosis, according to company documents reviewed by Reuters. Still the company kept mum.
It wasn’t until May 2015 – two years and four million prescriptions after Invokana hit the market – that the public first heard of the drug’s association with ketoacidosis. That’s when the U.S. Food and Drug Administration (FDA), learning of rising numbers of the dangerous episodes through its own reporting system, announced an investigation. It and European regulators subsequently ordered that a warning be added to the label on Invokana and more recent entrants to this new class of drugs, known as SGLT2 inhibitors.
Medtronic’s stock price falls nearly 9% following FDA warning letter was reported by Ricky Zipp for MedTechDive.com, 17 December 2021.
Medtronic’s stock price has fallen by nearly 9% since the company announced its diabetes group headquarters received an FDA warning letter following a facility inspection. Along with the stock hit, the company has been downgraded by several Wall Street firms. Wells Fargo and J.P. Morgan lowered their ratings of the company due to the warning letter and other recent setbacks in key product categories, such as renal denervation and its surgical robot Hugo.
One crucial question for Medtronic’s diabetes group is whether the warning letter is going to delay the regulatory process for the MiniMed 780G insulin pump, an important product for the company as it continues to lose ground in the diabetes tech space.
Insulin Pump Improves Glycemic Control but Increases Fat in Type 1 Diabetes was reported by Brandon May for EndocrinologyAdvisor.com, 16 December 2021.
In children and adolescents with type 1 diabetes (T1D), those who switched from multiple daily injections to an insulin pump showed significant improvement in glycemic control but increased body adiposity over time, according to study findings published in Pediatric Diabetes. The study was an analysis of data from the prospective, multicenter SWEET (Better control in Pediatric and Adolescent diabeteS: Working to crEate CEnTers of Reference) diabetes patient registry.
The investigators concluded that their findings “emphasize the role of diabetes technology in improving glucose control in [a] pediatric population with T1D but also the need for developing further strategies to prevent excess fat accumulation such as improved education programs on nutrition habits and mealtime routines”.
The Algorithm That (Recently) Changed the World was shared by Ella Alderson for Medium.com/Predict, 9 December 2021. This is just a fascinating read and possibly very revolutionary!
Earlier this year, an algorithm was released online — full and completely free — for academics to use. This algorithm represents one of the most important scientific discoveries of our lifetimes, showcasing the growing potential for AI to alter the course of our civilization. Using deep learning and neural networks the algorithm known as Alpha Fold promises to revolutionize the field of biochemistry. It can help us better understand diseases, formulate medicine, and produce solutions to everything from plastic pollution to excess carbon in the atmosphere. By attempting to solve the protein-folding problem we’ve made an exciting and unprecedented breakthrough that will affect the lives of us all.
The protein-folding problem has been an ongoing obstacle for the past 50 years. It first arose in 1972: a new theory proposed that knowing a protein’s amino acid sequence should allow you to fully predict its structure.
Proteins aren’t just fundamental to life, they are responsible for almost all the processes that take place inside a cell. All living organisms rely on these complex molecules. In turn, a protein is made of a chain of 20 different amino acids. The interactions between these amino acids determine how the protein will fold into its 3D shape. The shape of a protein plays a large role in determining its function, hence why in biology there is the saying, “structure is function”. Structure will determine what a protein will do and how it will work.
A single protein can be made of up to 2,000 amino acids. Determining all of their possible structures can take longer than the age of the entire universe. This amounts to some 10³⁰⁰ possibilities, meaning that a system capable of predicting how a protein folds will have to use something far more elegant and precise than simple brute force.
Ever since the competition known as the Critical Assessment of protein Structure Prediction began in 1994, no competing team has come even close to making accurate predictions. The competition itself consists of hundreds of teams whose algorithms aim to predict the structure of about 100 different proteins from given sequences of amino acids.
Last year, DeepMind’s Alpha Fold algorithm became the first to make increasingly accurate predictions. The algorithm made strides so astonishing that, to many researchers, the protein-folding problem has essentially been solved.
Alpha Fold’s predictions were on average over 90% accurate in 2020. This is a huge improvement over the average of 40% accuracy achieved by the top performing CASP teams over the last couple of decades.