The first AI-designed drugs have ended with disappointment.

Over the last year-plus, the first handful of molecules created by artificial intelligence have failed trials or been deprioritized. The AI companies behind these drugs brought them into the clinic full of fanfare about a new age of drug discovery — and have quietly shelved them after learning old lessons about how hard pharmaceutical R&D can be.

Earlier this month, UK-based Exscientia slipped into a pipeline update that a Phase I/II study of its cancer drug candidate EXS-21546 was winding down. That cut followed a decision last year by its partner Sumitomo Pharma to abandon another of its AI-designed drugs. In April, a test of BenevolentAI’s dermatitis drug fell short as well. And Recursion Pharmaceuticals — the third of AI’s early generation — hasn’t recorded a trial failure but has had a handful of clinical setbacks that don’t necessarily bode well.

There’s no shortage of AI naysayers, and the 0-for-3 start suggests that AI hype has set unrealistic expectations. Clinical wins are rarities in biotech, where an estimated 5% or 10% of drugs that head into human testing actually get approved.

“If you take the hype and PR at face value over the last 10 years, you would think it goes from 5% to 90%,” Patrick Malone, a principal at KdT Ventures, said of AI. “But if you know how these models work, it goes from 5% to maybe 6% or 7%.”

These three companies have been at this for roughly a decade, combining to rack up an accumulated deficit of over $1.5 billion.

Ivan Griffin

The reality check of the clinic, paired with a dour biotech market, has beaten up these first-generation biotechs that went public in 2021 or 2022. Their stock prices are all down at least 75%, underperforming the biotech market, even as new AI startups have continued to raise substantial sums of money. Generate:Biomedicines, Inceptive, Iambic and Genesis, for instance, have combined to raise $673 million over the past few months.

Executives at these first-generation companies say it’s too early for a verdict on whether or not AI boosts the odds of success, particularly given the vast likelihood that any drug candidate — AI-developed or not — will fail.

“The things that are easiest to show — speed and cost, particularly on the preclinical — have been done,” Ivan Griffin, BenevolentAI’s co-founder and chief operating officer, said in an interview with Endpoints News. Increasing the probability of success “will inevitably take the longest to prove out.”

Milestone moments to quiet cancellations

Back in the final days of January 2020, as Covid-19 was emerging as a pandemic threat, Exscientia CEO Andrew Hopkins hailed a “key milestone in drug discovery.”

His biotech announced the first AI-designed drug had entered the clinic. Its partner Sumitomo led the Phase I study in obsessive-compulsive disorder, with the Financial Times calling the trial’s start a “critical milestone for the role of machine learning in medicine.”

About two years later, in January 2022, Sumitomo disclosed they had abandoned the drug, which failed to meet the study’s criteria. In an interview, Hopkins said Exscientia’s job was to just design the molecule, with Sumitomo making the clinical decisions.

Exscientia had more control over the next drug, a cancer treatment called EXS-21546, which it brought into the clinic in December 2020. Earlier this month, the biotech said it was discontinuing an ongoing Phase I/II study with modeling suggesting “it will be challenging for ‘546 to reach a suitable therapeutic index.”

Andrew Hopkins

Hopkins said that the trial didn’t fail, as the biotech doesn’t have full results back.

“It wasn’t a clinical data decision,” he said. “It was a strategic decision” to prioritize two other cancer drugs that the company believes have better chances.

“We don’t want to be one of those companies that keeps pushing a program forward because it’s the only thing they have,” Hopkins said.

Clinical failure is less contestable for BenevolentAI, a fellow UK-based AI enthusiast whose lead drug was unable to beat a placebo in a Phase IIa atopic dermatitis study, the biotech announced earlier this year. That readout led to the drug’s end, a stock plunge, and sizable layoffs.

Recursion stands apart as the only one of the three to maintain a valuation above $1 billion today. (Exscientia is worth about $650 million, while BenevolentAI is valued at $117 million.)  The biotech has had several positive Phase I readouts centered on safety and tolerability, such as a C. diff drug recently clearing a healthy volunteer study of 42 people. The company used AI to identify existing compounds rather than design new drugs for its early pipeline.

Dylan Reid

“The market has never known what to make of these companies,” said Dylan Reid, a partner at Zetta Venture Partners. “They’ve been way too excited and way too down. At one point, they value the platform at X billions of dollars, and today, it’s probably a drag on valuation.”

While Recursion hasn’t had a clinical failure, its development plans have had hiccups. It quietly dropped a rare disease drug last year, citing “noise in the potency” and delays in getting a trial going. Earlier this month, the Salt Lake City-based biotech slimmed down an ongoing Phase II study for another of its drugs, dropping a placebo arm and cutting expected enrollment to 37 people. A spokesperson said the changes will help get to data and Phase III faster.

If a decade sounds too soon to judge these biotechs, consider Recursion’s leaders set that timeline themselves, publicly declaring the goal of discovering 100 clinical-stage drug candidates in its first 10 years. Roughly 10 years on, Recursion’s pipeline has four clinical-stage molecules.

Recursion expects two Phase II readouts in the second half of 2024. All three biotechs have ongoing partnerships with drugmaking giants like Merck, Bristol Myers Squibb, and Roche’s Genentech.

The AI clinical pipeline is full of other players as well, such as Verge Genomics’ ALS drug, BPGbio’s brain cancer treatment, Insilico Medicine’s idiopathic pulmonary fibrosis drug, Generate:Biomedicines’ Covid-19 antibody, and Auransa’s liver cancer therapy.

Strategies evolve as more players emerge

AI backers say successful programs like Moderna’s Covid-19 vaccine or Nimbus Therapeutics’ TYK2 inhibitor used AI to a degree. But those drugmakers don’t brand those medicines as AI-designed, while Exscientia, BenevolentAI, and Recursion market their approach as AI-driven or AI-enabled.

A decade in, leaders of the first-generation companies say they are still learning.

BenevolentAI, for instance, says its failed atopic dermatitis drug candidate didn’t use the company’s target identification approach, which is behind its ulcerative colitis drug that entered the clinic earlier this year.

Exscientia has incorporated more human tissue samples in its research process and hired experienced clinical hands like Michael Krams, Hopkins said.

“We’ve also now realized if we want to change the probability of success in the clinic, it’s not just better molecules,” Hopkins said. “We also need better translational models.”

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Australian equity investors enamoured with the study of consumer behaviour might take an interest in the cycling industry, especially as it impacts the ASX-listed Flight Centre (ASX: FLT).

To many, including those in the cycling industry itself, the surge in demand during the pandemic was a complete surprise. What happens next might offer important insights into many retail sectors beyond cycling.

The cycling industry in the U.S. and worldwide was once a hubbub of frenzied activity and an intense boom between 2020 and 2022. Today, however, the industry seems to be taking a “big exhale,” as some industry insiders have remarked. Experts had anticipated a decline after the pandemic-inspired boom, but its duration and magnitude remain uncertain.

The global pandemic sent shockwaves across various sectors, with bicycle retailers experiencing unprecedented turbulence. Once familiar with the annual rhythms of a seasonal business, bicycle stores suddenly faced an overwhelming surge in demand, dwindling product availability thanks to fractured supply chains, and a daily grind (pun intended) defined by unpredictability (Figure 1.).

Figure 1. June 2020 year-on-year sales performance of key bike categories

Source: The NPD Group

And Figure 1., reflects the surge in sales in the first few months of the pandemic, which continued for nearly two more years.

Three years after this unpredictable surge, its aftermath, as revealed by Figure 2., is still evident. As the industry gradually transitions back to what feels like “business as usual”, the landscape of the industry has evolved significantly.

Figure 2. Real U.S. personal consumption expenditure on bicycles and accessories ($U.S.)

Fresh faces entered the market, while established giants took audacious steps that garnered varied responses. Retailers who ventured into stockpiling and digital commerce at the pandemic’s onset reaped exponential revenue growth. In contrast, those who couldn’t adapt swiftly often struggled with the sudden and overwhelming demand.

In an email to customers and investors, niche Denver-based brand, Rodeo Labs, offered insight into the most recent reverberations in industry dynamics, noting, “we’re operating in one of the least settled periods in the bike industry”.

The most recent tumult became evident in late 2022, a time which typically sees a seasonal slowdown due to the onset of colder, darker winter months in the northern hemisphere. For Rodeo Labs, the question as to whether they would face the same challenges as larger companies in the industry was answered by early summer, when “there was a palpable decrease in energy in the global bike party.”

The shift wasn’t limited to bike sales. Major cycling events, once selling out almost instantly, are witnessing slower registrations. The once-popular trend of large group rides seems to be making way for smaller, more intimate rides, with many participants even opting for other activities entirely.

Reflecting on this change, Rodeo Labs observed, “I think there just isn’t as much interest in ‘events’ as there was in previous years. People seem less inclined to spend money to go on a ride with a bunch of other people than they were 12-24 months ago.” Sponsored athletes also seem to be moving away from events, with many focusing more on other careers.

With the cycling community seeing significant shifts, bike companies are grappling with the change. “In the next six months, you’re going to see a number of bike companies fail,” an industry representative reportedly shared with Rodeo Labs earlier this year. Denver recently bid farewell to Guerilla Gravity brand, a promising brand that showcased the feasibility of scaling bike production in the U.S. While the exact reasons remain undisclosed, many brands have faced challenges with inventory and financial constraints, a fact that has become a subject of industry talk.

And that talk is not restricted to the U.S.. Here, in Australia, booming COVID sales were also met with a shortage of stock and furloughed manufacturing in Taiwan. Massive orders were submitted to meet the demand, but those orders are only being delivered now, when demand has slumped.

The Australian Financial Review (AFR) recently reported the value of Brisbane-based 99 Bikes-owner Pedal Group, which is unlisted and 47 per cent owned by Flight Centre, 22 per cent owned by Flight Centre CEO Graham Turner and 15 per cent owned by his son Matt, has “almost halved since the peak of cycling mania during the coronavirus pandemic, as an oversupply of bicycles bites.”

After generating earnings before interest and tax (EBIT) of $51.6 million in 2021 and $18.7 million in 2022, as pandemic lockdown orders triggered massive demand for bikes, Pedal Group posted EBIT of $5.5 million in the 2023 financial year and an overall loss of $12.4 million.

According to documents seen by the AFR, Pedal Group is now valued at about $127 million, following a planned issue of equity to staff at $5.18 a share, which is down materially from $10.73 a share in November 2021.

Consumer bicycle buying behaviour through the pandemic and following its conclusion, is reflected across a range of leisure equipment industries. The extent to which operators can cancel orders made during the height of the buying boom will determine, in many instances, who survives. Those that do will reap the rewards not only of a return to stable conditions but also a larger share of the market.

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Researchers at the University of Cincinnati have developed a lateral flow assay that can detect bacterial toxins from Porphyromonas gingivalis, the causative bacteria for gingivitis. The technology could make it easier and faster to identify early-stage gingivitis, which can lead to periodontitis and eventual tooth loss, as well as contributing to a variety of other diseases such as stroke and heart disease. The lateral flow assay requires a small saliva sample, and can provide results very quickly, but does require the saliva sample to be pre-treated with potato starch to deactivate salivary amylase, an enzyme that can interfere with the assay.

The humble lateral flow assay grew in prominence during the COVID-19 pandemic as a quick at-home method to check your COVID status, but this technology was already a staple of such applications as pregnancy testing. Now, researchers are increasingly aware of its utility as a rapid point-of-care diagnostic technology and are beginning to apply it to the detection of other diseases. In this instance, these researchers at the University of Cincinnati have developed a lateral flow assay to detect the bacteria responsible for gingivitis.

Gingivitis is caused by P. gingivalis, which typically starts as mild gum inflammation. However, this can spread to other parts of the periodontal tissue, causing damage to soft tissue and bone that stabilize our teeth. This damage can eventually lead to tooth loss. Moreover, researchers have also linked P. gingivalis to other conditions, including cardiovascular diseases, rheumatoid arthritis, and even neurodegenerative diseases such as Alzheimer’s disease.  

There are lab-based tests available to detect P. gingivalis, but compared with a lateral flow test, they are complex, slow, expensive, and lack portability. If a diagnostic technique is too expensive, time consuming and inconvenient, then patients or clinicians will only tend to seek it out or recommend it if symptoms have already developed. However, for routine testing and health screening, a convenient, rapid, and point-of-care test is much preferred. A lateral flow test for gingivitis, for example, could be administered by a dentist every time someone undergoes a routine dental checkup.   

The assay detects a bacterial endotoxin released into the saliva by P. gingivalis through a simple immunoassay, whereby antibodies capture and identify the toxin. An enzyme present in saliva called amylase can interfere with this, so the assay requires the saliva to be pretreated with potato starch to deactivate this enzyme. In the future, you may be able to use such lateral flow assays to conveniently detect a wide variety of pathogens and biomarkers, and you can thank SARS-CoV-2 for the privilege.  

Study in journal Sensors & Diagnostics: Salivary endotoxin detection using combined mono/polyclonal antibody-based sandwich-type lateral flow immunoassay device

Via: University of Cincinnati

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