Pfizer has released mid-stage (Phase 2b) VESPER-3 results: its experimental drug PF’3944 (previously known as MET-097i and brought into Pfizer via the Metsera deal) helped people with obesity or overweight lose up to 12.3% of body weight (placebo-adjusted) by week 28. The headline feature is the dosing schedule: patients started with weekly injections during dose escalation, then switched to a once-monthly maintenance shot. Pfizer says there was no clear weight-loss “plateau” by week 28, and the trial continues through week 64.
Author: Dzmitry Korsak
Dzmitry Korsak
Experienced journalist and editor with over 25 years in the field. His work focuses on medical technologies, social issues, and innovation. He values an evidence-based approach, thorough work with primary sources, and the ability to communicate complex topics in a clear and accessible way.
Inflation, exchange rates, sanctions, market panics—we dream of “calculating” all this in the era of big data. But in the case of any major economic crisis, the chain of human reactions (how officials, businesses, and consumers behave) is so unique and sometimes illogical that it breaks any model. In this interview, we’ll break down what AI can already do in economics and where it still “stumbles” over real life.
AI in pharma and life sciences is an easy “sell,” yet delivering real value remains a formidable challenge. Progress is most often hampered by closed data, weak data sharing, and inflated expectations. In this interview with Marcin Wawryszczuk (PhD, MBA) — Head of AI at Andersen and an AI researcher — we discuss how data platforms are becoming the bottleneck, whether it is possible to distinguish a viable project from a mere demo, and why, in production, resilience to drift and explainability of results outweigh impressive metrics.
The genre of the LLM interview emerged the moment the first model was released to the public. Since then, “artificial intelligence” has been asked to prophesy the future, debate the philosophical nature of being, or simply engage in heart-to-hearts. This creates the illusion of conversation with a sentient being — a phenomenon that simultaneously frightens, astonishes, and inspires awe. Yet, we have never encountered an interview where the AI is addressed honestly, with its mask of humanity stripped away.
Recently, an article titled “How the AI ‘bubble’ compares to history” was published in the Financial Times; its author, Jonathan Vincent, reminds us of economic crises…
Artificial intelligence has rapidly become a working tool in companies, government administration, education, and everyday services within just a few years. As AI becomes more…
AI remote patient monitoring seeks to address a longstanding and complex challenge in medicine: translating chaotic streams of health data into a comprehensible and standardized format. This capability empowers medical professionals to prioritize effectively and respond to challenges in a timely manner. The primary “superpower” of AI is transforming a thousand signals, ex. heart rate spikes, into a single, actionable notification: “Pay attention, there is a problem!”
Today, AI is simultaneously a religion and an irritant: some hope that humanity has gotten its hands on a tool for explosive development; for others, the very disclaimer “made by artificial intelligence” already causes irritation. People worry that LLM will take jobs away from millions and, in the longer run, will become a superintelligence that will enslave humanity. And more and more often we hear that multibillion-dollar infusions into the industry are inflating a bubble that will soon burst.
Japan’s Dai Nippon Printing has unexpectedly set its sights on a market where until now one name has reigned supreme — ASML. The Dutch company controls around 90% of the global lithography equipment market and effectively holds a monopoly on EUV scanners, without which the most advanced chips are impossible. All modern electronics — from AI data centers to smartphones — quite literally depend on a single company and its machines.
As recently as yesterday, 32 GB of RAM for a PC was a routine purchase; today it looks like a full-fledged investment appreciating faster than gold and certainly faster than bitcoin. What is increasingly resembles a brewing crisis: the race to ramp up AI capacity is often coming at the expense of other sectors, and manufacturers whose products have had the good fortune to become coveted in this race are quick to reshuffle priorities, with little concern for the consequences for ordinary users.