Funding, Deals & Partnerships: BIOLOGICS & MEDICAL DEVICES; BioMed e-Series; Medicine and Life Sciences Scientific Journal – http://PharmaceuticalIntelligence.com
Clarivate was formed in 2016, following the acquisition of Thomson Reuters‘ Intellectual Property and Science business by Onex Corporation and Baring Private Equity Asia. Clarivate has acquired various companies since then, including, notably, ProQuest in 2021.
Clarivate (formerly CPA Global) was formerly the Intellectual Property and Science division of Thomson Reuters. Before 2008, it was known as Thomson Scientific. In 2016, Thomson Reuters struck a $3.55 billion deal in which they spun it off as an independent company, and sold it to private-equity firms Onex Corporation and Baring Private Equity Asia.
June 1, 2017: Publons, a platform for researchers to share recognition for peer review.
April 10, 2018: Kopernio, AI-tech startup providing ability to search for full-text versions of selected scientific journal articles.
October 30, 2018: TrademarkVision, provider of Artificial Intelligence (AI) trademark research applications.
September 9, 2019: SequenceBase, provider of patent sequence information and search technology to the biotech, pharmaceutical and chemical industries.
December 2, 2019: Darts-ip, provider of case law data and analytics for intellectual property (IP) professionals.
January 17, 2020: Decision Resources Group (DRG), a leading healthcare research and consulting company, providing high-value healthcare industry analysis and insights.
June 22, 2020: CustomersFirst Now, in intellectual property (“IP”) software and tech-enabled services.
October 1, 2020: CPA Global, intellectual property (“IP”) software and tech-enabled services.
December 1, 2021: ProQuest, software, data and analytics provider to academic, research and national institutions.[27]It was acquired for $5.3 billion from Cambridge Information Group in what was described as a “huge deal in the library and information publishing world”. The company said that the operational concept behind the acquisition was integrating ProQuest’s products and applications with Web of Science. Chairman of ProQuest Andy Snyder became the vice chairman of Clarivate. The Scholarly Publishing and Academic Resources Coalition, an advocacy group for open access to scholarship, voiced antitrust concerns. The acquisition had been delayed mid-year due to a Federal Trade Commission antitrust probe.
We are a leading global information services and analytics company serving the scientific research, intellectual property and life sciences end-markets. We provide structured information and analytics to facilitate the discovery, protection and commercialization of scientific research, innovations and brands. Our product porfolio includes well-established market-leading brands such as Web of Science, Derwent Innovation, Life Sciences, CompuMark and MarkMonitor (which they later divested). We believe that the stron balue proposition of our content, user interfaces, visualization and analytical tools, combined with the integration of our products and services into customers’ daily workflows, leads to our substantial customer loyalty as evidenced by their willingness to renew subscriptions with us.
Our structure, enabling a sharp focus on cross-selling opportunities within markets, is comprised of two product groups:
Science Group: consists of Web of Science and Life Science Product Lines
Intellectual Property Group: consists of Derwent, CompuMark and MarkMonitor
Corporations, government agencies, universities, law firms depend on our high-value curated content, analytics and services. Unstructured data has grown exponentially over the last decade. The trend has resulted in a critical need for unstructured data to be meaningfully filtered, analyzed and curated into relvent information that facilitates key operational and strategic decision making. Our highly curated, proprietary information created through our sourcing, aggregation, verification, translation, and categorization (ONTOLOGY) of data has resulted in our solutions being embedded in our customers’ workflow and decision-making processes.
Overview of Clarivate PLC five year strategy in 2019. Note that in 2019 the Science Group accounted for 56.2% of revenue! This was driven by their product Cortellis!
Figure. Overview of Clarivate PLC five year strategy in 2019. Note that in 2019 the Science Group accounted for 56.2% of revenue! This was driven by their product Cortellis!
Also Note nowhere in the M&A Discussion in years before 2023 was anything mentioned concerning AI or Large Language Models.
The Clarivate of Today: Built for Life Sciences with Cortellis
Clarivate PLC has integrated multiple platforms into their offering Cortellis, which integrated AI and LLM into the structured knowledge bases (see more at https://clarivate.com/products/cortellis-family/)
“Life sciences organizations are tasked, now more than ever, to discover and develop treatments that challenge the status quo, increase ROI, and improve patient lives. However, its become increasingly difficult to find, integrate and analyze the key data your teams need to make critical decisions and get your Cortellis products to patients faster.
Cortellis Competitive Intelligence: maximize ROI and improve patient outcomes
Cortellis Deals Intelligence: Portfolio Strategy and Business Development (find best deal)
Cortellis Clinical Intelligence: Clinical Trial Support and Regulatory
Cortellis Digital Health Intelligence: understand digital health ecosystem
Cortellis Drug Discovery: improve drug development speed and efficiency
MetaBase and MetaCore: integrated omics knowledge bases for drug discovery
Cortellis Regulatory: help with filings
Cortellis HTA: health tech compliance (HIPAA)
CMC Intelligence: new drug marketing
Generics Intelligence
Drug Safety Intelligence: both preclinical safety and post marketing pharmacovigilence
Watch Videos on Cortellis for Drug Discovery
Watch Video on Qiagen Site to see how Cortellis Integrates with Qiagen Omics Platform IPA with Clarivate Meta Core to gain more insights into genomic and proteomic data
Understand complex ‘omics data to accelerate your research
Discover why QIAGEN Ingenuity Pathway Analysis (IPA) is the leading pathway analysis application among the life science research community and is cited in tens of thousands of articles for the analysis, integration and interpretation of data derived from ‘omics experiments. Such experiments include:
RNA-seq
Small RNA-seq
Metabolomics
Proteomics
Microarrays including miRNA and SNP
Small-scale experiments
With QIAGEN IPA you can predict downstream effects and identify new targets or candidate biomarkers. QIAGEN Ingenuity Pathway Analysis helps you perform insightful data analysis and interpretation to understand your experimental results within the context of various biological systems.
Articles Relevant to Drug Development, Natural Language Processing in Drug Development, and Clarivate on this Open Access Scientific Journal Include:
Live Notes from JP Morgan Healthcare Conference Virtual Endpoints Preview: January 8-9 2024
Reporter: Stephen J. Williams, Ph.D.
Endpoints at #JPM24 | Primed to unlock biopharma’s next dealmaking wave
Endpoints at JP Morgan Healthcare Conference
January 8-9 | San Francisco, CA80 Mission St, San Francisco, CA
An oasis has emerged in the biopharma money desert as backers look to replenish capital — still, uncertainty remains on whether it’s a mirage or the much needed dealmaking bump the industry needs. Yet spirits run high as JPM24 marks the triumphant return of inking strategic alliances and peering into the industry crystal ball — while keeping an eye out for some major M&A.
We’re back live from San Francisco for JPM Monday and Tuesday — our calendar of can’t-miss panels and fireside chats will feature prominent biopharma leaders to watch. The Endpoints Hub provides the ultimate coworking space with everything you need — 1:1 and group meeting spots plus guest pass capabilities and more. Join us in-person at the Endpoints Hub or watch online to stay plugged into all the action.
8 JAN
Welcome remarks
8:05 AM – 8:25 AM PST
Pfizer vet Mikael Dolsten has some thoughts on Big Pharma R&D
Endpoints News founding editor John Carroll will sit down with longtime Pfizer CSO Mikael Dolsten to talk about Pfizer’s pipeline, what he’s learned on the job about preclinical research and development and what’s ahead for the pharma giant in drug development and deals.
Mikael Dolsten
Chief Scientific Officer, President, Pfizer Research & Development
Pfizer
Pfizer Mikael Dolsten: Pfizer produced a series of AI generated molecules with new properties. Sees rapid adoption of AI in the area of drug discovery and molecular design.
8:25 AM – 9:05 AM PST
What pharma wants: The industry’s dealmakers look ahead at 2024
The drug industry’s appetite for new assets hasn’t slowed down. Top business development execs will give their outlook on the year, what they’re looking for and how they see the market.
Glenn Hunzinger
Pharmaceutical & Life Sciences Consulting Solutions Leader
PwC US
Rachna Khosla
SVP, Head of Business Development
Amgen
James Sabry
Global Head of Pharma Partnering
Roche
Devang Bhuva
SVP, Corporate Development
Gilead Sciences, Inc.
Endpoints News
Dealmaking panel
Glenn Hunzinger: if you do not have a GLP1 will have a tough time getting a good market price for your company; capital markets are not where they want to be; sees a tough deal making climate like last year. The problem with many biotech companies are they are coming earlier to the venture capital because of greater funding needs and so it is imperative that they articulate the potential of their company in scientific detail
Rachna Khosla: Make sure your investors are not just CAPITAL PARTNERS but use their expertise and involve them in development issues you may have, especially ones that a young firm will face. The problem is most investments assume what the future looks like (for example how antibody drug conjugates, once a field left for dead, has been rejuvenated because of advances in chemistry).
James Sabry: noted that cardiac and metabolic drugs are now at the focus of many investors, especially with the new anti-obesity drugs on market
Devang Bhuva: Most deals we see start as collaborations or partnerships. You want to involve an alliance management team early in the deal making process. This process could take years.
9:05 AM – 9:20 AM PST
The IPO: How Apogee Therapeutics went public in the most challenging market in years
Not many biotechs went public in 2023. And of those that did, not many have had a great time of it. Apogee is the exception and our panel will offer a behind-the-scenes look at their decision to enter the market and what life is like as a young public company.
Michael Henderson
CEO
Apogee Therapeutics
Kyle LaHucik
MODERATOR
Senior Reporter
Endpoints News
Michael Henderson: Not many biotech IPOs deals happened in 2023. Michael feels it is because too many biotechs focused on building platforms, which was a hard sell in 2023. He felt not many biotechs had clear milestones and investors wanted a clear primary validated target. He said many biotech startups are in a funding crunch and most need at least $440M on their balance sheet to get to 2026.
9:50 AM – 10:10 AM PST
Top predictions for biotech in 2024
Catalent CEO Alessandro Maselli will be back at the big JPM healthcare confab to talk with Endpoints News founder John Carroll about their top predictions of what’s coming up for the biotech industry in 2024. The stakes couldn’t be higher as the industry grapples with headwinds and new opportunities in a gale of market forces. Two top observers share their thoughts on the year ahead.
Alessandro Maselli
President & CEO
Catalent
10:15 AM – 10:35 AM PST
Innovation at a crossroads: Keys to unlocking the value of science and technology
The industry has long discussed the promise of technology and the acceleration it provides in scientific advancement and across the industry value chain. However, the promise of its impact has yet to fully be realized. This discussion will outline the keys to unleashing this promise and the implications and actions to be taken by the biopharmaceutical companies across the industry.
Ray Pressburger
North America Life Sciences Industry Lead & Global Life Sciences Strategy Lead
Accenture
SPONSORED BY
10:35 AM – 11:05 AM PST
Activism and Investing: In conversation with Elliott Investment Management’s Marc Steinberg
Elliott has been behind many of 2023’s highest-profile healthcare investments, including multiple activist engagements and taking Syneos Health private. What has made large healthcare companies such interesting investment opportunities for firms like Elliott? What’s Elliott’s investing strategy in healthcare? And what should companies expect when an activist calls?
Marc Steinberg
Senior Portfolio Manager
Elliott Investment Management
Andrew Dunn
MODERATOR
Biopharma Correspondent
Endpoints News
11:05 AM – 11:35 AM PST
Creating ROI from AI
AI is predicted to transform the way drugs are made, from discovery to clinical trials to market. But beyond the initial hype and early adoption, where has AI made meaningful contributions to R&D? How does it help drug developers advance science? Endpoints publisher Arsalan Arif is convening a panel of leading experts to discuss the state of AI in the pharmaceutical landscape and the outlook for 2024. How does AI impact the drug pipeline, from the early steps of discovery to reducing trial failure rate?
Thomas Clozel
Co-Founder & CEO
Owkin
Venkat Sethuraman
SVP, Global Biometrics & Data Sciences
Bristol Myers Squibb
Frank O. Nestle
Global Head of Research & Chief Scientific Officer
Sanofi
Matthias Evers
Chief Business Officer
Evotec
Arsalan Arif
MODERATOR
Founder & Publisher
Endpoints News
SPONSORED BY
11:35 AM – 12:00 PM PST
Biopharma’s dealmaker: Behind the scenes with Centerview Partners co-president Eric Tokat
Almost every major biopharma deal in 2023 had Centerview’s name attached to it. And much of the time, Eric Tokat was the banker making those deals happen. Hear his outlook for 2024, how transactions are getting done and what’s placed his firm at the center of so much action.
E. Eric Tokat
Co-President, Investment Banking
Centerview Partners
CenterView Partners Eric Tokat feels dealmaking will improve in 2024, given the recent flurry of dealmaking at end of last year and right before main JPM Healthcare Conference. He says Centerview wants to help the biotechs they invest in on their strategic path. This may translate into buyers more actively involved (more than startups want) and buyers now are in the drivers seat as far as the timeline of deals and development.
Is the megamerger dead for this year? He says it is very hard to see two major mergers happening but there will be many smaller and mid size biotech deals happening, but these deals will be more speculative in nature.. The focus for large pharma is top line growth. Most of the buyers have an infrastructure and value is more of buying and dropping it in their business so there is now a huge emphasis on due diligence on whether synergies exist or not
12:00 PM – 12:30 PM PST
Founder, legend, leader: In conversation with Nobel laureate Carolyn Bertozzi
Carolyn Bertozzi’s discoveries around bioorthogonal chemistry won the Nobel Prize in Chemistry in 2022 and are at the heart of new therapies being tested in patients. Join us as we discuss what inspires her and where she sees the next big advances.
Carolyn Bertozzi
Prof. of Chemistry, Stanford University and Baker Family Director of Sarafan ChEM-H
Stanford University
Nicole DeFeudis
MODERATOR
Editor
Endpoints News
Bioorthogonal chemistry: class of high yielding chemical reactions that proceed rapidly and selectively in biological environments without side reactions toward endogenous functions. This is also a type of ‘click chemistry’ in biological system where only specifically alter the biomolecule of interest.
Orthogonal: two chemicals not interacting with each other
Dr. Bertozzi noted she has started a new Antibody-Drug-Conjugate (ADC) company which involves designing with biorthogonal chemistry to make new functional molecules with varying properties
She noted hardly any biologists knew anything about glycobiology when she first started. However now she feels pharma and academia are working very well with each other
Bioorthogonal and Click Chemistry Curated by Prof. Carolyn R. Bertozzi, 2022 winner of the Nobel Prize in Chemistry
The 2022 Nobel Prize in Chemistry has been awarded jointly to ACS Central Science Editor-in-Chief, Carolyn R. Bertozzi of Stanford University, Morten Meldal of the University of Copenhagen, and K. Barry Sharpless of Scripps Research, for the development of click chemistry and bioorthogonal chemistry.
To celebrate this remarkable achievement, 2022 Nobel Prize winner Professor Carolyn R. Bertozzi has curated this Bioorthogonal and Click Chemistry Virtual Issue, highlighting papers published across ACS journals that have built upon the foundational work in this exciting area of chemistry.
Bioorthogonal reactions are chemical reactions that neither interact with nor interfere with a biological system. The participating functional groups must be inert to biological moieties, must selectively reactive with each other under biocompatible conditions, and, for in vivo applications, must be nontoxic to cells and organisms. Additionally, it is helpful if one reactive group is small and therefore minimally perturbing of a biomolecule into which it has been introduced either chemically or biosynthetically. Examples from the past decade suggest that a promising strategy for bioorthogonal reaction development begins with an analysis of functional group and reactivity space outside those defined by nature. Issues such as stability of reactants and products (particularly in water), kinetics, and unwanted side reactivity with biofunctionalities must be addressed, ideally guided by detailed mechanistic studies. Finally, the reaction must be tested in a variety of environments, escalating from aqueous media to biomolecule solutions to cultured cells and, for the most optimized transformations, to live organisms.
9 JAN
9:40 AM – 10:10 AM PST
Biotech downturn survival school
Our panelists have seen the worst, and made it through to the other side. Join us for downturn survival school as our panelists talk about what sets apart the ones who make it through tough times.
These panalists think it will be specialist capital year to shine while the general capital is still sitting on the sidelines
JJ Kang
CEO
Appia Bio
“2023 was a tough year while 2020 was a boon year to start a company. We will continue to see these cycles; many of these new CEOs have never seen a biotech downturn yet and may not know how to preserve capital for the downturn”.
“Doing a partnership with Kite Pharmaceuticals early in our startp allowed us to get work done without risking a lot of capital, even if it means equity and asset dilution. That makes sense. However even if you are small insist on being an equal partner.”
“There are many investors we talk to who do not want to invest in cell therapy. Too risky now”
Carl Gordon
Managing Partner
OrbiMed Advisors
There are many macroeconomic factors affecting investment and capital today which will carry on through 2024. Not raising money when you do not need money is a bad philosophy. Always bbe raising captial. This is especially true when you have to rely on hedge funds. Parnerships howeve are sometimes the only way for small biotechs to leverage their strengths.
Joshua Boger
Executive Chair
Alkeus Pharmaceuticals, Inc.
Boger: Expect volatility for 2024. This environment feels very different than past downturns.
Even in downturns there is still lots of capital; remember access to human capital is better in a downturn and is easier to access; however it has become harder to get drug approvals
The panelists agree that access to capital and funding will be as tricky in 2024 than 2023. They did
suggest that a new funding avenue, private credit, may be a source of capital. This is discussed below:
When thinking about a private alternative investment asset class, the first thing that springs to mind is private equity. But there’s one more asset class with the word private in its name that has recently gained much attention. We’re talking about private credit.
Indeed, this once little-known investment strategy is now growing rapidly in popularity, offering private investors worldwide an exciting opportunity to diversify their portfolio with, in theory, less risky investments that yield significant returns.
Private credit investments refer to investors lending money to companies who then repay the loan at a given interest rate within the predetermined period.
The private credit market has grown significantly over the past years, rising from $875 million in 2020 to $1.4 trillion at the beginning of 2023.
Please WATCH VIDEO BY GOLDMAN SACHS ON PRIVATE CREDIT
The New Molecule: How breakthrough technologies are actually changing pharma R&D
Join us for a look at how AI, machine learning and generative technologies are actually being applied inside drugmakers’ labs. We’ll explore how new technologies are being used, their implications, how they intersect with regulatory and IP issues and how this fast-changing field is likely to evolve.
Kailash Swarna
Managing Director & Global Life Sciences Clinical Development Lead
Accenture
Artificial Intelligence is making impact in a grand way on biology in three aspects:
Speeding up target validation: now we can get through 300 molecules a day
Predicition like AlphaFold is doing; molecular simulations
Document submission especially with regulatory and IND submissions
Pamela Carroll
COO
Isomorphic Labs formerly of AlphaFold
We were first with Novartis at last year JPM and was one year old but parnering with them in that initial year was very important for sealing the deal.
They are looking now at neurologic diseases like ALS. She wondered whether ALS is actually multiple diseases and we need to stratify patients like we do in oncology trials. Their main competion is the whole tech world like Amazon, Google and other Machine Learning companies so being a tech player in the biotech world means you are not just competing with other biotechs but large tech companies as well.
Jorge Conde
General Partner
Andreessen Horowitz
Need is still great for drug discovery; early adopters show AI tools can be used in big pharma. There are lots of applications of AI in managing care; a lot of back office applications including patient triaging. He does not see big AI mergers with pharma companies – this will be mainly partnerships not M&A deals
Alicyn Campbell
Chief Scientific Officer
Evinova, a Healthtech Subsidiary of the AstraZeneca Group
There is a need to turn AI for real world example. For example AI tools were used in clinical trials to determine patient cohorts with pneumonitis. At Evinova they are determining how AI can hel[p show clinical benefit with respect to efficacy and safety
Joshua Boger at #JPM24 (Brian Benton Photography)
January 12, 2024 09:06 AM ESTUpdated 10:00 AM PeopleStartups
Vertex founder Joshua Boger on surviving downturns, ‘painful’ partnerships, and the importance of culture: #JPM24
While the JP Morgan Healthcare Conference was full of voices of measured optimism, rooting for the market to bounce back in 2024, one longtime biotech leader warned against setting any firm expectations.
Instead of predicting when the downturn may end, Vertex Pharmaceuticals founder Joshua Boger said he advises biotech leaders to expect — and plan for — volatility. Speaking Tuesday on an Endpoints News panel alongside OrbiMed’s Carl Gordon and Appia Bio CEO JJ Kang, Boger shared lessons learned on surviving downturns, striking pharma deals, and the importance of keeping a company’s culture based on his two decades of founding and leading Vertex as CEO from 1989 to 2009. The 72-year-old is now serving as executive chairman of Alkeus Pharmaceuticals, a startup developing a rare disease drug.
“I never experienced a straight line up,” Boger said. “Everything had its cycles, and it was how you respond to the cycle, not by predicting when the end is going to be, but just by responding to the present situation.”
At Boger’s first appearance at the JP Morgan conference in 1991, he said the conference’s theme was the end of biotech financing. Just a few months later, Regeneron successfully went public, rapidly changing the outlook for the whole field.
“We had no idea we were ever going to take public money,” he said. “When Regeneron did their IPO, we went, ‘Whoa, there’s something happening here,’ and we pivoted quickly.”
Vertex went public later that year. Throughout his 20-year tenure, Boger said no pharma company ever made an acquisition offer for Vertex, which now commands a market value of $110 billion and recently won the first FDA approval for a CRISPR gene editing therapy.
“We had an uber corporate policy to always make ourselves more expensive than anyone would stomach,” Boger said.
However, Vertex did strike a range of partnerships with Big Pharmas, which Boger described as a painful but necessary part of running a biotech startup.
“It’s impossible for a partnership not to slow you down,” he said. “You can and should try as hard as you can not to do that, but just count on it. They’ll slow you down.”
Boger said startups should insist on being equal partners in pharma deals, at least making sure they have a seat at a partner’s development meetings.
“Realize they’re going to be painful, it’s going to be horrible, and you need to do it,” Boger said.
While Vertex suffered through layoffs, stock price plunges, and trial failures, Boger credited a focus on culture as key to its long-term success.
“It’s the most important ingredient for a successful company,” he said. “Technology is acquirable. Culture is not acquirable. There are 10 companies that will fail because of culture for every one that succeeds, and the successful companies in retrospect will almost always have special cultural aspects that kept them through those downtimes.”
JPM24 opens with ADCs the hottest ticket in San Francisco
The overall deal flow in biopharma tapered off in 2023 but the big companies sure know what they want (what they really, really want), according to a new report from J.P. Morgan.
And that’s antibody-drug conjugates, which drove a fourth-quarter spike in licensing deal proceeds and provided a glimmer of hope to an industry battered by outside forces and grim financing prospects.
J.P. Morgan’s annual 2023 Biopharma Licensing and Venture Report arrived on the eve of the firm’s famous conference, which is set to welcome thousands of attendees in San Francisco today—East Coast weather permitting.
2023 was tough, but clinical biotechs still had a lot of opportunities to wheel and deal, according to J.P. Morgan. While licensing deals, venture investments, M&A and IPOs were down overall in the fourth quarter, deal values stayed fairly high thanks to a flurry of late-stage tie ups.
Follow the Fierce team’s coverage of the 2024 J.P. Morgan Healthcare Conference here.
Biopharma licensing partnerships accounted for $63 billion in total value during the fourth quarter from 108 deals. Just one deal—Merck’s ADC partnership with Daiichi Sankyo—accounted for $22 billion of that. Another huge one was another ADC bet, with Bristol Myers Squibb signing on to work with SystImmune for a total value of $8.4 billion. If you exclude the Merck deal, the total value of these partnerships is still higher than the previous quarter, which ended with $32.1 billion.
The total number of licensing deals compares to 149 in the same quarter a year earlier, 195 for Q4 2021 and 223 for Q4 2022.
As for venture investments, the year closed out with $17 billion total across 250 rounds, thanks to $3.5 billion earned through 79 rounds in the last quarter. Aiolos Bio snagged the title of largest venture round of the quarter with $245 million, which also proved to be the largest series A, too.
There was just one IPO in all of the fourth quarter—Cargo Therapeutics making the plunge for $300 million—and 13 overall for the year. It’s a far cry from the heyday of 2021 and experts are still unsure what 2024 will hold. J.P. Morgan reported $2.5 billion raised from 12 completed biopharma IPOs for the year on Nasdaq and NYSE. Nine out of the 12 companies had clinical programs when they took the leap to the public markets. As of December 13, five of the companies were trading above their IPO price.
As for M&A, December saw a rush of Big Pharmas snapping up companies around Christmas. J.P. Morgan tallied the fourth quarter at $37.6 billion and $128.8 billion across 112 total acquisitions for all of 2023.
AbbVie was the top buyer of the quarter with the two largest acquisitions thanks to the $10 billion outlay for ImmunoGen and $8.7 billion buy of Cerevel Therapeutics.
All of this adds up to 270 total deals in the fourth quarter total, which is lower than the third quarter which exceeded 300.
J.P. Morgan sees some big potential for smaller biopharmas looking for licensing partners, as Big Pharmas have been handing out larger upfront payments for the deals they really want.
Cancer was once again the most in-demand therapeutic areas, reaching a new height of $86.1 billion in 2023. Followed by $21.1 billion for neurological disorders.
For More Articles on Real Time Conference Coverage in this Open Access Scientific Journal see:
Eight Subcellular Pathologies driving Chronic Metabolic Diseases – Methods for Mapping Bioelectronic Adjustable Measurements as potential new Therapeutics: Impact on Pharmaceuticals in Use
In this curation we wish to present two breaking through goals:
Goal 1:
Exposition of a new direction of research leading to a more comprehensive understanding of Metabolic Dysfunctional Diseases that are implicated in effecting the emergence of the two leading causes of human mortality in the World in 2023: (a) Cardiovascular Diseases, and (b) Cancer
Goal 2:
Development of Methods for Mapping Bioelectronic Adjustable Measurements as potential new Therapeutics for these eight subcellular causes of chronic metabolic diseases. It is anticipated that it will have a potential impact on the future of Pharmaceuticals to be used, a change from the present time current treatment protocols for Metabolic Dysfunctional Diseases.
According to Dr. Robert Lustig, M.D, an American pediatric endocrinologist. He is Professor emeritus of Pediatrics in the Division of Endocrinology at the University of California, San Francisco, where he specialized in neuroendocrinology and childhood obesity, there are eight subcellular pathologies that drive chronic metabolic diseases.
These eight subcellular pathologies can’t be measured at present time.
In this curation we will attempt to explore methods of measurement for each of these eight pathologies by harnessing the promise of the emerging field known as Bioelectronics.
Unmeasurable eight subcellular pathologies that drive chronic metabolic diseases
Glycation
Oxidative Stress
Mitochondrial dysfunction [beta-oxidation Ac CoA malonyl fatty acid]
Insulin resistance/sensitive [more important than BMI], known as a driver to cancer development
Membrane instability
Inflammation in the gut [mucin layer and tight junctions]
Epigenetics/Methylation
Autophagy [AMPKbeta1 improvement in health span]
Diseases that are not Diseases: no drugs for them, only diet modification will help
Image source
Robert Lustig, M.D. on the Subcellular Processes That Belie Chronic Disease
These eight Subcellular Pathologies driving Chronic Metabolic Diseases are becoming our focus for exploration of the promise of Bioelectronics for two pursuits:
Will Bioelectronics be deemed helpful in measurement of each of the eight pathological processes that underlie and that drive the chronic metabolic syndrome(s) and disease(s)?
IF we will be able to suggest new measurements to currently unmeasurable health harming processes THEN we will attempt to conceptualize new therapeutic targets and new modalities for therapeutics delivery – WE ARE HOPEFUL
In the Bioelecronics domain we are inspired by the work of the following three research sources:
Michael Levin is an American developmental and synthetic biologist at Tufts University, where he is the Vannevar Bush Distinguished Professor. Levin is a director of the Allen Discovery Center at Tufts University and Tufts Center for Regenerative and Developmental Biology. Wikipedia
THE VOICE of Dr. Justin D. Pearlman, MD, PhD, FACC
PENDING
THE VOICE of Stephen J. Williams, PhD
Ten TakeAway Points of Dr. Lustig’s talk on role of diet on the incidence of Type II Diabetes
25% of US children have fatty liver
Type II diabetes can be manifested from fatty live with 151 million people worldwide affected moving up to 568 million in 7 years
A common myth is diabetes due to overweight condition driving the metabolic disease
There is a trend of ‘lean’ diabetes or diabetes in lean people, therefore body mass index not a reliable biomarker for risk for diabetes
Thirty percent of ‘obese’ people just have high subcutaneous fat. the visceral fat is more problematic
there are people who are ‘fat’ but insulin sensitive while have growth hormone receptor defects. Points to other issues related to metabolic state other than insulin and potentially the insulin like growth factors
At any BMI some patients are insulin sensitive while some resistant
Visceral fat accumulation may be more due to chronic stress condition
Fructose can decrease liver mitochondrial function
A methionine and choline deficient diet can lead to rapid NASH development
Acinetobacter baumannii bacteria that are resistant to important antibiotics called carbapenems. Acinetobacter baumannii are highly-drug resistant bacteria that can cause a range of infections for hospitalized patients, including pneumonia, wound, or blood infections.
Pseudomonas aeruginosa, which are resistant to carbapenems. Pseudomonas aeruginosa can cause skin rashes and ear infectious in healthy people but also severe blood infections and pneumonia when contracted by sick people in the hospital.
Enterobacteriaceae — a family of bacteria that live in the human gut — that are resistant to both carbepenems and another class of antibiotics, cephalosporins.
It has been designated critical need for development of antibiotics to these pathogens. Now researchers at Mcmaster University and others in the US had used artificial intelligence (AI) to screen libraries of over 7,000 chemicals to find a drug that could be repurposed to kill off the pathogen.
Liu et. Al. (1) published their results of an AI screen to narrow down potential chemicals that could work against Acinetobacter baumanii in Nature Chemical Biology recently.
Abstract
Acinetobacter baumannii is a nosocomial Gram-negative pathogen that often displays multidrug resistance. Discovering new antibiotics against A. baumannii has proven challenging through conventional screening approaches. Fortunately, machine learning methods allow for the rapid exploration of chemical space, increasing the probability of discovering new antibacterial molecules. Here we screened ~7,500 molecules for those that inhibited the growth of A. baumannii in vitro. We trained a neural network with this growth inhibition dataset and performed in silico predictions for structurally new molecules with activity against A. baumannii. Through this approach, we discovered abaucin, an antibacterial compound with narrow-spectrum activity against A. baumannii. Further investigations revealed that abaucin perturbs lipoprotein trafficking through a mechanism involving LolE. Moreover, abaucin could control an A. baumannii infection in a mouse wound model. This work highlights the utility of machine learning in antibiotic discovery and describes a promising lead with targeted activity against a challenging Gram-negative pathogen.
Schematic workflow for incorporation of AI for antibiotic drug discovery for A. baumannii from 1. Liu, G., Catacutan, D.B., Rathod, K. et al. Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii. Nat Chem Biol (2023). https://doi.org/10.1038/s41589-023-01349-8
Antibiotics kill bacteria. However, there has been a lack of new drugs for decades and bacteria are becoming harder to treat, as they evolve resistance to the ones we have.
More than a million people a year are estimated to die from infections that resist treatment with antibiotics.The researchers focused on one of the most problematic species of bacteria – Acinetobacter baumannii, which can infect wounds and cause pneumonia.
You may not have heard of it, but it is one of the three superbugs the World Health Organization has identified as a “critical” threat.
It is often able to shrug off multiple antibiotics and is a problem in hospitals and care homes, where it can survive on surfaces and medical equipment.
Dr Jonathan Stokes, from McMaster University, describes the bug as “public enemy number one” as it’s “really common” to find cases where it is “resistant to nearly every antibiotic”.
Artificial intelligence
To find a new antibiotic, the researchers first had to train the AI. They took thousands of drugs where the precise chemical structure was known, and manually tested them on Acinetobacter baumannii to see which could slow it down or kill it.
This information was fed into the AI so it could learn the chemical features of drugs that could attack the problematic bacterium.
The AI was then unleashed on a list of 6,680 compounds whose effectiveness was unknown. The results – published in Nature Chemical Biology – showed it took the AI an hour and a half to produce a shortlist.
The researchers tested 240 in the laboratory, and found nine potential antibiotics. One of them was the incredibly potent antibiotic abaucin.
Laboratory experiments showed it could treat infected wounds in mice and was able to kill A. baumannii samples from patients.
However, Dr Stokes told me: “This is when the work starts.”
The next step is to perfect the drug in the laboratory and then perform clinical trials. He expects the first AI antibiotics could take until 2030 until they are available to be prescribed.
Curiously, this experimental antibiotic had no effect on other species of bacteria, and works only on A. baumannii.
Many antibiotics kill bacteria indiscriminately. The researchers believe the precision of abaucin will make it harder for drug-resistance to emerge, and could lead to fewer side-effects.
In principle, the AI could screen tens of millions of potential compounds – something that would be impractical to do manually.
“AI enhances the rate, and in a perfect world decreases the cost, with which we can discover these new classes of antibiotic that we desperately need,” Dr Stokes told me.
The researchers tested the principles of AI-aided antibiotic discovery in E. coli in 2020, but have now used that knowledge to focus on the big nasties. They plan to look at Staphylococcus aureus and Pseudomonas aeruginosa next.
“This finding further supports the premise that AI can significantly accelerate and expand our search for novel antibiotics,” said Prof James Collins, from the Massachusetts Institute of Technology.
He added: “I’m excited that this work shows that we can use AI to help combat problematic pathogens such as A. baumannii.”
Prof Dame Sally Davies, the former chief medical officer for England and government envoy on anti-microbial resistance, told Radio 4’s The World Tonight: “We’re onto a winner.”
She said the idea of using AI was “a big game-changer, I’m thrilled to see the work he (Dr Stokes) is doing, it will save lives”.
Other related articles and books published in this Online Scientific Journal include the following:
Series D: e-Books on BioMedicine – Metabolomics, Immunology, Infectious Diseases, Reproductive Genomic Endocrinology
The Vibrant Philly Biotech Scene: Recent Happenings & Deals
Curator: Stephen J. Williams, Ph.D.
As the office and retail commercial real estate market has been drying up since the COVID pandemic, commercial real estate developers in the Philadelphia area have been turning to the health science industry to suit their lab space needs. This includes refurbishing old office space as well as new construction.
Gattuso secures $290M construction loan for life sciences building on Drexel campus
By Ryan Mulligan – Reporter, Philadelphia Business Journal
Dec 19, 2022
Gattuso Development Partners and Vigilant Holdings of New York have secured a $290 million construction loan for a major life sciences building set to be developed on Drexel University’s campus.
The funding comes from Houston-based Corebridge Financial, with an additional equity commitment from Boston-based Baupost Group, which is also a partner on the project. JLL’s Capital Markets group arranged the loan.
Plans for the University City project at 3201 Cuthbert St. carry a price tag of $400 million. The 11-story building will total some 520,000 square feet, making it the largest life sciences research and lab space in the city when it comes online.
The building at 3201 Cuthbert will rise on what had served as a recreation field used by Drexel and is located next to the Armory. Gattuso Development, which will lease the parcel from Drexel, expects to to complete the project by fall 2024. Robert A.M. Stern Architects designed the building.
A rendering of a $400 million lab and research facility Drexel University and Gattuso Development Partners plan to build at 3201 Cuthbert St. in Philadelphia.
The building is 45% leased by Drexel and SmartLabs, an operator of life sciences labs. Drexel plans to occupy about 60,000 square feet, while SmartLabs will lease two floors totaling 117,000 square feet.
“We believe the project validates Philadelphia’s emergence as a global hub for life sciences research, and we are excited to begin construction,” said John Gattuso, the co-founder and president of Philadelphia-based Gattuso Development.
Ryan Ade, Brett Segal and Christopher Peck of JLL arranged the financing.
Tmunity CEO Usman Azam departing to lead ‘stealth’ NYC biotech firm
By John George – Senior Reporter, Philadelphia Business Journal
Feb 7, 2022
The CEO of one of Philadelphia’s oldest cell therapy companies is departing to take a new job in the New York City area.
Usman “Oz” Azam, who has been CEO of Tmunity Therapeutics since 2016, will lead an unnamed biotechnology company currently operating in stealth mode.
In a posting on his LinkedIn page, Azam said, “After a decade immersed in cell therapies and immuno-oncology, I am now turning my attention to a new opportunity, and will be going back to where I started my life sciences career in neurosciences.”
Tmunity, a University of Pennsylvania spinout, is looking to apply CAR T-cell therapy, which has proved to be successful in treating liquid cancers, for the treatment of solid tumors.
Last summer, Tmunity suspended clinical testing of its lead cell therapy candidate targeting prostate cancer after two patients in the study died. Azam, in an interview with the Business Journal in June, said the company, which had grown to about 50 employees since its launch in 2015, laid off an undisclosed number of employees as a result of the setback.
Azam said on LinkedIn he is still a big believer in CAR T-cell therapy, noting Tmunity co-founder Dr. Carl June and his colleagues at Penn just published in Nature the 10-year landmark clinical outcomes study with the first CD19 CAR-T patients and programs.
“It’s just the beginning,” he stated. “I’m excited about the prospect of so many new cell- and gene-based therapies emerging in the next five to 10 years to tackle many solid and liquid tumors, and I hope we all continue to see the remarkable impact this makes on patients and families around the world.”
Azam could not be reached for comment Monday. Tmunity has engaged a search firm to identify his successor.
Tmunity, which is based in Philadelphia, has its own manufacturing operations in East Norriton. Tmunity’s founders include June and fellow Penn cell therapy pioneer Bruce Levine, who led the development of a CAR T-cell therapy now marketed by Novartis as Kymriah, a treatment for certain types of blood cancers.
In therapy using CAR-T cells, a patient’s T cells — part of their immune system — are removed and genetically modified in the laboratory. After they are re-injected into a patient, the T cells are better able to attack and destroy tumors. CAR is an acronym for chimeric antigen receptor. Chimeric antigen receptors are receptor proteins that have been engineered to give T cells their improved ability to target tumors.
Jodie Harris is a Philadelphia native who has spent the last 15 years in the U.S. Department of Treasury.
By Ryan Mulligan – Reporter, Philadelphia Business Journal
The Philadelphia Industrial Development Corp. has tapped U.S. Department of Treasury veteran Jodie Harris to be its next president.
Harris succeeds Anne Bovaird Nevins, who spent 15 years in the organization and took over as president in January 2020 before stepping down at the end of last year. Executive Vice President Sam Rhoads has been interim president.
Harris, a Philadelphia native who currently serves as director of the Community Development Financial Institutions Fund for the Department of Treasury, was picked after a regional and national search and will begin her tenure as president on June 1. She becomes the 12th head of PIDC and the first African-American woman to lead the organization.
PIDC is a public-private economic development corporation founded by the city and the Chamber of Commerce for Greater Philadelphia in 1958. It mainly uses industrial and commercial real estate projects to attract jobs, foster business opportunities and spur overall community growth. The organization has spurred over $18.5 billion in financing across its 65 years.
In a statement, Harris said that it is “a critical time for Philadelphia’s economy.”
“I’m especially excited for the opportunity to lead such an important and impactful organization in my hometown of Philadelphia,” Harris said. “As head of the CDFI Fund, I know first-hand what it takes to drive meaningful, sustainable, and equitable economic growth, especially in historically underserved communities.”
Harris is a graduate of the University of Maryland and received an MBA and master of public administration from New York University. In the Treasury Department, Harris’ most recent work aligns with PIDC’s economic development mission. At the Community Development Financial Institutions Fund, she oversaw a $331 million budget, mainly comprised of grant and administrative funding for various economic programs. Under Harris’ watch, the fund distributed over $3 billion in pandemic recovery funding, its highest level of appropriated grants ever.
Harris has been a part of the Treasury Department for 15 years, including as director of community and economic development policy.
In addition to government work, Harris has previously spent time in the private, academia and nonprofit sectors. In the beginning of her career, Harris worked at Meridian Bank and Accenture before turning to become a social and education policy researcher at New York University. She also spent two years as president of the Urban Business Assistance Corporation in New York.
Mayor Jim Kenney said that Philadelphia is “poised for long-term growth” and Harris will help drive it.
Real estate company SkyREM plans to spend $250 million converting the historic Quartermaster site in South Philadelphia to a life sciences campus with restaurants and a hotel.
The redevelopment would feature wet and dry lab space for research, development and bio-manufacturing.
The renamed Quartermaster Science + Technology Park is near the southwest corner of Oregon Avenue and South 20th Street in the city’s Girard Estates neighborhood. It’s east of the Quartermaster Plaza retail center, which sold last year for $100 million.
The 24-acre campus is planned to have six acres of green space, an Aldi grocery store opening by March and already is the headquarters for Indego, the bicycle share program in Philadelphia.
Six buildings totaling 1 million square feet of space would be used for research and development labs. There’s 500,000 square feet of vacant space available for life sciences and high technology companies with availabilities as small as 1,000 square feet up to 250,000 square feet contiguous. There’s also 150,000 square feet of retail space available.
The office park has 200,000 square feet already occupied by tenants. The Philadelphia Job Corps Center and Delaware Valley Intelligence Center are tenants at the site.
A rendering shows part of the Quartermaster Science + Technology Park as a redeveloped mixed-use life science campus.
QUARTERMASTER / PROVIDED BY FIFTEEN
The campus was previously used by the military as a place to produce clothing, footwear and personal equipment during World War I and II. The clothing factory closed in 1994. The Philadelphia Quartermaster Depot was listed on the National Register of Historic Places in 2010.
“We had a vision to preserve the legacy of this built-to-last historic Philadelphia landmark and transform it to create a vibrant space where the best and brightest want to innovate, collaborate, and work,” SkyREM CEO and Founder Alex Dembitzer said in a statement.
SkyREM, a real estate investor and developer, has corporate offices in New York and Philadelphia. The company acquired the site in 2001.
Vered Nohi, SkyREM’s regional executive director of new business development, called the redevelopment “transformational” for Philadelphia.
SkyREM announced the redevelopment of the Quartermaster campus in South Philadelphia into a life sciences campus with restaurants and a hotel. This rendering looks across Oregon Avenue toward the southwest corner of Oregon and 21st Street.
QUARTERMASTER / PROVIDED BY FIFTEEN
Quartermaster would join a wave of new life sciences projects being developed in the surrounding area and across the region.
The site is near both interstates 76 and 95 and is about 2 miles north of the Philadelphia Navy Yard, which has undergone a similar transformation from a military hub to a major life sciences and mixed-use redevelopment project. The Philadelphia Industrial Development Corp. is also in the process of selecting a developer to create a massive cell and gene therapy manufacturing complex across two sites totaling about 40 acres on Southwest Philadelphia’s Lower Schuylkill riverfront.
A rendering shows part of the future Quartermaster Science and Technology Park in South Philadelphia. The 24-acre campus is planned to have six buildings with 1 million square feet of life science space.
QUARTERMASTER / PROVIDED BY FIFTEEN
SkyREM is working with Maryland real estate firm Scheer Partners to lease the science and technology space. Philadelphia’s MPN Realty will handle leasing of the retail space. Architecture firm Fifteen is working on the project’s design.
Scheer Partners Senior Vice President Tim Conrey said the Quartermaster conversion will help companies solve for “speed to market” as demand for life science space in the region has been strong.
Brandywine Realty Trust originally planned to redevelop a Radnor medical office into lab and office space, split 50-50 between the two uses.
After changes in demand for lab and office space, Brandywine (NYSE: BDN) recently completed the 168,000-square-foot, four-story building at 250 King of Prussia Road in Radnor fully for life sciences.
“The pipeline is now 100% life sciences, which, while requiring more capital, is also generating longer term leases at a higher return on cost,” Brandywine CEO Jerry Sweeney of the project said during the company’s fourth-quarter earnings call on Thursday.
At the same time, Brandywine is holding off on developing new office buildings unless it has a tenant lined up in advance.
The shift reflects how Philadelphia-based Brandywine continues to lean into — and bet big — on life sciences.
Brandywine is the city’s largest owner of trophy office buildings and has several major development projects in the works. The company is planning to eventually develop 3 million square feet of life sciences space. For now, 800,000 square feet of life sciences space is under development, including a 12-story, 417,000-square-foot life sciences building at 3151 Market St. and a 29-story building with 200,000 square feet of life sciences space at 3025 John F. Kennedy Blvd. Both are part of the multi-phase Schuylkill Yards project underway near 30th Street Station in University City.
Once its existing projects are completed, Brandywine would have 800,000 square feet of life sciences space, making up 8% of its portfolio.Sweeney said the company wants to grow that figure to 21%.
Brandywine is developing a 145,000-square-foot, build-to-suit office building at 155 King of Prussia Road in Radnor for Arkema, a France-based global supplier of specialty materials. The building will be Arkema’s North American headquarters. Construction began in January and is scheduled to be completed in late 2024.
Brandywine reported that since November it raised over $705 million through fourth-quarter asset sales, an unsecured bond transaction and a secured loan. The company has “complete availability” on its $600 million unsecured line of credit, Sweeney said.
Brandywine sold a 95% leased, 86,000-square-foot office building at 200 Barr Harbor Drive in West Conshohocken for $30.5 million. The company also sold its 50% ownership interest in the 1919 Market joint venture for $83.2 million to an undisclosed buyer. 1919 Market St. is a 29-story building with apartments, office and commercial space. Brandywine co-developed the property with LCOR and the California State Teacher’s Retirement System.
Brandywine declined to comment and LCOR could not be reached.
Brandywine’s core portfolio is 91% leased.
The project at 250 King of Prussia Road cost $103.7 million and was recently completed. The renovation included 12-foot high floor-to-ceiling glass on the second floor, a new roof, lobby, elevator core, common area with a skylight and an added structured parking deck.
Located in the Radnor Life Science Center, a new campus with nearly 1 million square feet of lab, research and office space, Sweeney said it’s a “magnet” for biotech companies. Avantor, a global manufacturer and distributor of life sciences products, is headquartered in the complex.
Sweeney said Brandywine is “very confident” demand will stay strong for life sciences in Radnor. The building at 250 King of Prussia Road is projected to be fully leased by early 2024.
“Larger users we’re talking to, they just tend to take a little bit more time than we would like as they go through technical requirements and space planning requirements,” Sweeney said.
While Brandywine is aiming to increase its life sciences footprint, the company is being selective about what it builds next. The company may steer away from developments other than life sciences. The Schuylkill Yards project, for example, features a significant life sciences portion in University City.
“Other than fully leased build-to-suit opportunities, our future development starts are on hold,” Sweeney said, “pending more leasing on the existing joint venture pipeline and more clarity on the cost of debt capital and cap rates.”
Brandywine said about 70% to 75%of suburban tenants have returned to offices while that number has been around 50% in Philadelphia. At this point, though, it hasn’t yet affected demand when leasing space. Some tenants, for example, have moved out of the city while others have moved in.
In the fourth quarter, Brandywine had $55.7 million funds from operations, or 32 cents per share. That’s down from $60.4 million, or 35 cents per share, in the fourth quarter of 2021. Brandywine generated $129 million in revenue in the fourth quarter, up slightly from $125.5 in the year-ago period.
Brandywine stock is up 6.4% since the start of the year to $6.70 per share on Monday afternoon.
Many of Brandywine’s properties are in desirable locations, which have seen demand remain strong despite challenges facing offices, on par with industry trends.
Brandywine’s 12-story, 417,000-square-foot building at 3151 Market St. is on budget for $308 million and on schedule to be completed in the second quarter of 2024. Sweeney said Brandywine anticipates entering a construction loan in the second half of 2023, which would help complete the project. The building, being developed along with a global institutional investor,would be used for life sciences, innovation and office space as part of the larger Schuylkill Yards development in University City.
The company’s 29-story building at 3025 John F. Kennedy Blvd. with 200,000 square feet of life sciences space and 326 luxury apartments, is also on budget, costing $287.3 million, and on time, eyeing completion in the third quarter of this year.
Bacterial multidrug resistance problem solved by a broad-spectrum synthetic antibiotic
Reporter and Curator: Dr. Sudipta Saha, Ph.D.
There is an increasing demand for new antibiotics that effectively treat patients with refractory bacteremia, do not evoke bacterial resistance, and can be readily modified to address current and anticipated patient needs. Recently scientists described a promising compound of COE (conjugated oligo electrolytes) family, COE2-2hexyl, that exhibited broad-spectrum antibacterial activity. COE2-2hexyl effectively-treated mice infected with bacteria derived from sepsis patients with refractory bacteremia, including a CRE K. pneumoniae strain resistant to nearly all clinical antibiotics tested. Notably, this lead compound did not evoke drug resistance in several pathogens tested. COE2-2hexyl has specific effects on multiple membrane-associated functions (e.g., septation, motility, ATP synthesis, respiration, membrane permeability to small molecules) that may act together to abrogate bacterial cell viability and the evolution of drug-resistance. Impeding these bacterial properties may occur through alteration of vital protein–protein or protein-lipid membrane interfaces – a mechanism of action distinct from many membrane disrupting antimicrobials or detergents that destabilize membranes to induce bacterial cell lysis. The diversity and ease of COE design and chemical synthesis have the potential to establish a new standard for drug design and personalized antibiotic treatment.
Recent studies have shown that small molecules can preferentially target bacterial membranes due to significant differences in lipid composition, presence of a cell wall, and the absence of cholesterol. The inner membranes of Gram-negative bacteria are generally more negatively charged at their surface because they contain more anionic lipids such as cardiolipin and phosphatidylglycerol within their outer leaflet compared to mammalian membranes. In contrast, membranes of mammalian cells are largely composed of more-neutral phospholipids, sphingomyelins, as well as cholesterol, which affords membrane rigidity and ability to withstand mechanical stresses; and may stabilize the membrane against structural damage to membrane-disrupting agents such as COEs. Consistent with these studies, COE2-2hexyl was well tolerated in mice, suggesting that COEs are not intrinsically toxic in vivo, which is often a primary concern with membrane-targeting antibiotics. The COE refinement workflow potentially accelerates lead compound optimization by more rapid screening of novel compounds for the iterative directed-design process. It also reduces the time and cost of subsequent biophysical characterization, medicinal chemistry and bioassays, ultimately facilitating the discovery of novel compounds with improved pharmacological properties.
Additionally, COEs provide an approach to gain new insights into microbial physiology, including membrane structure/function and mechanism of drug action/resistance, while also generating a suite of tools that enable the modulation of bacterial and mammalian membranes for scientific or manufacturing uses. Notably, further COE safety and efficacy studies are required to be conducted on a larger scale to ensure adequate understanding of the clinical benefits and risks to assure clinical efficacy and toxicity before COEs can be added to the therapeutic armamentarium. Despite these limitations, the ease of molecular design, synthesis and modular nature of COEs offer many advantages over conventional antimicrobials, making synthesis simple, scalable and affordable. It enables the construction of a spectrum of compounds with the potential for development as a new versatile therapy for the emergence and rapid global spread of pathogens that are resistant to all, or nearly all, existing antimicrobial medicines.
2022 FDA Drug Approval List, 2022 Biological Approvals and Approved Cellular and Gene Therapy Products
Reporter: Aviva Lev-Ari, PhD, RN
SOURCE
Tal Bahar’s post on LinkedIn on 1/17/2023
Novel Drug Approvals for 2022
FDA’s Center for Drug Evaluation and Research (CDER)
New Molecular Entities (“NMEs”)
Some of these products have never been used in clinical practice. Below is a listing of new molecular entities and new therapeutic biological products that CDER approved in 2022. This listing does not contain vaccines, allergenic products, blood and blood products, plasma derivatives, cellular and gene therapy products, or other products that the Center for Biologics Evaluation and Research approved in 2022.
Others are the same as, or related to, previously approved products, and they will compete with those products in the marketplace. See Drugs@FDA for information about all of CDER’s approved drugs and biological products.
Certain drugs are classified as new molecular entities (“NMEs”) for purposes of FDA review. Many of these products contain active moieties that FDA had not previously approved, either as a single ingredient drug or as part of a combination product. These products frequently provide important new therapies for patients. Some drugs are characterized as NMEs for administrative purposes, but nonetheless contain active moieties that are closely related to active moieties in products that FDA has previously approved. FDA’s classification of a drug as an “NME” for review purposes is distinct from FDA’s determination of whether a drug product is a “new chemical entity” or “NCE” within the meaning of the Federal Food, Drug, and Cosmetic Act.
To treat adults with HIV whose HIV infections cannot be successfully treated with other available treatments due to resistance, intolerance, or safety considerations Press Release
To decrease the incidence of infection in patients with non-myeloid malignancies receiving myelosuppressive anti-cancer drugs associated with clinically significant incidence of febrile neutropenia
The Center for Biologics Evaluation and Research (CBER) regulates products under a variety of regulatory authorities. See the Development & Approval Process page for a description of what products are approved as Biologics License Applications (BLAs), Premarket Approvals (PMAs), New Drug Applications (NDAs) or 510Ks.
Biologics License Applications and Supplements
New BLAs (except those for blood banking), and BLA supplements that are expected to significantly enhance the public health (e.g., for new/expanded indications, new routes of administration, new dosage formulations and improved safety).
Other Applications Approved or Cleared by the Center for Biologics Evaluation and Research (CBER)
Medical devices involved in the collection, processing, testing, manufacture and administration of licensed blood, blood components and cellular products.
There are five FDA-approved CAR-T treatments for blood cancers and two gene therapies to treat rare diseases now on the market in the U.S. The late-stage pipeline could produce several more cancer CAR-Ts and gene therapies to treat a range of diseases.
One of the biggest races to watch in the cell therapy space will be that between Gilead Sciences’ Yescarta and Bristol Myers Squibb’s Breyanzi, both of which are gunning to move their CAR-Ts into earlier lines of treatment in large B-cell lymphoma (LBCL). At ASH, both companies rolled out impressive data from their trials in the second-line setting, but Gilead could have the upper hand by virtue of its three-year head start in the market, analysts said. Gilead expects to hear from the FDA on a label expansion in the second-line setting in April.
Proteolysis-targeting chimeras (PROTACs) are a promising new class of drugs that selectively degrade cellular proteins of interest. PROTACs that target oncogene products are avidly being explored for cancer therapies, and several are currently in clinical trials. Drug resistance is a substantial challenge in clinical oncology, and resistance to PROTACs has been reported in several cancer cell models. Here, using proteomic analysis, we found intrinsic and acquired resistance mechanisms to PROTACs in cancer cell lines mediated by greater abundance or production of the drug efflux pump MDR1. PROTAC-resistant cells were resensitized to PROTACs by genetic ablation of ABCB1 (which encodes MDR1) or by coadministration of MDR1 inhibitors. In MDR1-overexpressing colorectal cancer cells, degraders targeting either the kinases MEK1/2 or the oncogenic mutant GTPase KRASG12C synergized with the dual epidermal growth factor receptor (EGFR/ErbB)/MDR1 inhibitor lapatinib. Moreover, compared with single-agent therapies, combining MEK1/2 degraders with lapatinib improved growth inhibition of MDR1-overexpressing KRAS-mutant colorectal cancer xenografts in mice. Together, our findings suggest that concurrent blockade of MDR1 will likely be required with PROTACs to achieve durable protein degradation and therapeutic response in cancer.
INTRODUCTION
Proteolysis-targeting chimeras (PROTACs) have emerged as a revolutionary new class of drugs that use cancer cells’ own protein destruction machinery to selectively degrade essential tumor drivers (1). PROTACs are small molecules with two functional ends, wherein one end binds to the protein of interest, whereas the other binds to an E3 ubiquitin ligase (2, 3), bringing the ubiquitin ligase to the target protein, leading to its ubiquitination and subsequent degradation by the proteasome. PROTACs have enabled the development of drugs against previously “undruggable” targets and require neither catalytic activity nor high-affinity target binding to achieve target degradation (4). In addition, low doses of PROTACs can be highly effective at inducing degradation, which can reduce off-target toxicity associated with high dosing of traditional inhibitors (3). PROTACs have been developed for a variety of cancer targets, including oncogenic kinases (5), epigenetic proteins (6), and, recently, KRASG12C proteins (7). PROTACs targeting the androgen receptor or estrogen receptor are avidly being evaluated in clinical trials for prostate cancer (NCT03888612) or breast cancer (NCT04072952), respectively.
However, PROTACs may not escape the overwhelming challenge of drug resistance that befalls so many cancer therapies (8). Resistance to PROTACs in cultured cells has been shown to involve genomic alterations in their E3 ligase targets, such as decreased expression of Cereblon (CRBN), Von Hippel Lindau (VHL), or Cullin2 (CUL2) (9–11). Up-regulation of the drug efflux pump encoded by ABCB1—MDR1 (multidrug resistance 1), a member of the superfamily of adenosine 5′-triphosphate (ATP)–binding cassette (ABC) transporters—has been shown to convey drug resistance to many anticancer drugs, including chemotherapy agents, kinase inhibitors, and other targeted agents (12). Recently, PROTACs were shown to be substrates for MDR1 (10, 13), suggesting that drug efflux represents a potential limitation for degrader therapies. Here, using degraders (PROTACs) against bromodomain and extraterminal (BET) bromodomain (BBD) proteins and cyclin-dependent kinase 9 (CDK9) as a proof of concept, we applied proteomics to define acquired resistance mechanisms to PROTAC therapies in cancer cells after chronic exposure. Our study reveals a role for the drug efflux pump MDR1 in both acquired and intrinsic resistance to protein degraders in cancer cells and supports combination therapies involving PROTACs and MDR1 inhibitors to achieve durable protein degradation and therapeutic responses.
Fig. 1. Proteomic characterization of degrader-resistant cancer cell lines. (A) Workflow for identifying protein targets up-regulated in degrader-resistant cancer cells. Single-run proteome analysis was performed, and changes in protein levels among parent and resistant cells were determined by LFQ. m/z, mass/charge ratio. (B and C) Cell viability assessed by CellTiter-Glo in parental and dBET6- or Thal SNS 032–resistant A1847 cells treated with increasing doses of dBET6 (B) or Thal SNS 032 (C) for 5 days. Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. Growth inhibitory 50% (GI50) values were determined using Prism software. (D to G) Immunoblotting for degrader targets and downstream signaling in parental A1847 cells and their derivative dBET6-R or Thal-R cells treated with increasing doses of dBET6 or Thal SNS 032 for 4 hours. The dBET6-R and Thal-R cells were continuously cultured in 500 nM PROTAC. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 values, quantitating either (E) the dose of dBET6 that reduces BRD2, BRD3, or BRD4 or (G) the dose of Thal SNS 032 that reduces CDK9 protein levels 50% of the DMSO control treatment, were determined with Prism software. Pol II, polymerase II. (H to K) Volcano plot of proteins with increased or reduced abundance in dBET6-R (H) or Thal-R (I) A1847 cells relative to parental cells. Differences in protein log2 LFQ intensities among degrader-resistant and parental cells were determined by paired t test permutation-based adjusted P values at FDR of <0.05 using Perseus software. The top 10 up-regulated proteins in each are shown in (J) and (K), respectively. FC, fold change. (L and M) ABCB1 log2 LFQ values in dBET6-R cells from (H) and Thal-R cells from (I) compared with those in parental A1847 cells. Data are presented as means ± SD from three independent assays. By paired t test permutation-based adjusted P values at FDR of <0.05 using Perseus software, ***P ≤ 0.001. (N) Cell viability assessed by CellTiter-Glo in parental and MZ1-resistant SUM159 cells treated with increasing doses of MZ1 for 5 days. Data were analyzed as % of DMSO control, presented as means of three independent assays. GI50 values were determined using Prism software. (O and P) Immunoblotting for degrader targets and downstream signaling in parental or MZ1-R SUM159 cells treated with increasing doses of MZ1 for 24 hours. The MZ1-R cells were continuously cultured in 500 nM MZ1. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 values were determined in Prism software. (Q and R) Top 10 up-regulated proteins (Q) and ABCB1 log2 LFQ values (R) in MZ1-R cells relative to parental SUM159 cells
Fig. 2. Chronic exposure to degraders induces MDR1 expression and drug efflux activity. (A) ABCB1 mRNA levels in parental and degrader-resistant cell lines as determined by qRT-PCR. Data are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (B) Immunoblot analysis of MDR1 protein levels in parental and degrader-resistant cell lines. Blots are representative of three independent experiments. (C to E) Immunofluorescence (“IF”) microscopy of MDR1 protein levels in A1847 dBET6-R (C), SUM159 MZ1-R (D), and Thal-R A1847 cells (E) relative to parental cells. Nuclear staining by DAPI. Images are representative of three independent experiments. Scale bars, 100 μm. (F) Drug efflux activity in A1847 dBET6-R, SUM159 MZ1-R, and Thal-R A1847 cells relative to parental cells (Par.) using rhodamine 123 efflux assays. Bars are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (G) Intracellular dBET6 levels in parental or dBET-R A1847 cells transfected with a CRBN sensor and treated with increasing concentrations of dBET6. Intracellular dBET6 levels measured using the CRBN NanoBRET target engagement assay. Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. *P ≤ 0.05, **P ≤ 0.01, and ***P ≤ 0.001 by Student’s t test. (H and I) FISH analysis of representative drug-sensitive parental and drug-resistant A1847 (H) and SUM159 (I) cells using ABCB1 and control XCE 7 centromere probes. Images of interphase nuclei were captured with a Metasystems Metafer microscope workstation, and the raw images were extracted and processed to depict ABCB1 signals in magenta, centromere 7 signals in cyan, and DAPI-stained nuclei in blue. (J and K) CpG methylation status of the ABCB1 downstream promoter (coordinates: chr7.87,600,166-87,601,336) by bisulfite amplicon sequencing in parent and degrader-resistant A1847 (J) and SUM159 (K) cells. Images depict the averaged percentage of methylation for each region of the promoter, where methylation status is depicted by color as follows: red, methylated; blue, unmethylated. Schematic of the ABCB1 gene with the location of individual CpG sites is shown. Graphs are representative of three independent experiments. (L and M) Immunoblot analysis of MDR1 protein levels after short-term exposure [for hours (h) or days (d) as indicated] to BET protein degraders dBET6 or MZ1 (100 nM) in A1847 (L) and SUM159 (M) cells, respectively. Blots are representative of three independent experiments. (N to P) Immunoblot analysis of MDR1 protein levels in A1847 and SUM159 cells after long-term exposure (7 to 30 days) to BET protein degraders dBET6 (N), Thal SNS 032 (O), or MZ1 (P), each at 500 nM. Blots are representative of three independent experiments. (Q and R) Immunoblot analysis of MDR1 protein levels in degrader-resistant A1847 (Q) and SUM159 (R) cells after PROTAC removal for 2 or 7 days. Blots are representative of three independent experiments.
Fig. 3. Blockade of MDR1 activity resensitizes degrader-resistant cells to PROTACs. (A and B) Cell viability by CellTiter-Glo assay in parental and degrader-resistant A1847 (A) and SUM159 (B) cells transfected with control siRNA or siRNAs targeting ABCB1 and cultured for 120 hours. Data were analyzed as % of control, presented as means ± SD of three independent assays. ***P ≤ 0.001 by Student’s t test. (C and D) Immunoblot analysis of degrader targets after ABCB1 knockdown in parental and degrader-resistant A1847 (C) and SUM159 (D) cells. Blots are representative, and densitometric analyses using ImageJ are means ± SD of three blots, each normalized to the loading control, GAPDH. (E) Drug efflux activity, using the rhodamine 123 efflux assay, in degrader-resistant cells after MDR1 inhibition by tariquidar (0.1 μM). Data are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (F to H) Cell viability by CellTiter-Glo assay in parental and dBET6-R (F) or Thal-R (G) A1847 cells or MZ1-R SUM159 cells (H) treated with increasing concentrations of tariquidar. Data are % of DMSO control, presented as means ± SD of three independent assays. GI50 value determined with Prism software. (I to K) Immunoblot analysis of degrader targets after MDR1 inhibition (tariquidar, 0.1 μM for 24 hours) in parental and degrader-resistant A1847 cells (I and J) and SUM159 cells (K). Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. (L and M) A 14-day colony formation assessed by crystal violet staining of (L) A1847 cells or (M) SUM159 cells treated with degrader (0.1 μM; dBET6 or MZ1, respectively) and MDR1 inhibitor tariquidar (0.1 μM). Images are representative of three biological replicates. (N) Immunoblotting for MDR1 in SUM159 cells stably expressing FLAG-MDR1 after selection with hygromycin. (O) Long-term 14-day colony formation assay of SUM159 cells expressing FLAG-MDR1 that were treated with DMSO, MZ1 (0.1 μM), or MZ1 and tariquidar (0.1 μM) for 14 days, assessed by crystal violet staining. Representative images of three biological replicates are shown. (P and Q) RT-PCR (P) and immunoblot (Q) analysis of ABCB1 mRNA and MDR1 protein levels, respectively, in parental or MZ1-R HCT116, OVCAR3, and MOLT4 cells.
Fig. 4. Overexpression of MDR1 conveys intrinsic resistance to degrader therapies in cancer cells. (A) Frequency of ABCB1 mRNA overexpression in a panel of cancer cell lines, obtained from cBioPortal for Cancer Genomics using Z-score values of >1.2 for ABCB1 mRNA levels (30). (B) Immunoblot for MDR1 protein levels in a panel of 10 cancer cell lines. Blots are representative of three independent experiments. (C) Cell viability by CellTiter-Glo assay in cancer cell lines expressing high or low MDR1 protein levels and treated with Thal SNS 032 for 5 days. Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. GI50 values were determined with Prism software. (D to F) Immunoblot analysis of CDK9 in MDR1-low (D) or MDR1-high (E) cell lines after Thal SNS 032 treatment for 4 hours. Blots are representative, and densitometric analyses using ImageJ are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value determined with Prism. (G and H) Immunoblotting of control and MDR1-knockdown DLD-1 cells treated for 4 hours with increasing concentrations of Thal SNS 032 [indicated in (H)]. Blots are representative, and densitometric analysis data are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value determined with Prism. (I) Drug efflux activity using rhodamine 123 efflux assays in DLD-1 cells treated with DMSO or 0.1 μM tariquidar. Data are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (J) Intracellular Thal SNS 032 levels, using the CRBN NanoBRET target engagement assay, in MDR1-overexpressing DLD-1 cells treated with DMSO or 0.1 μM tariquidar and increasing doses of Thal SNS 032. Data are % of DMSO control, presented as means ± SD of three independent assays. **P ≤ 0.01 and ***P ≤ 0.001 by Student’s t test. (K to N) Immunoblotting in DLD-1 cells treated with increasing doses of Thal SNS 032 (K and L) or dBET6 (M and N) alone or with tariquidar (0.1 μM) for 4 hours. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value of Thal SNS 032 for CDK9 reduction (L) or of dBET6 for BRD4 reduction (N) determined with Prism. (O to T) Bliss synergy scores based on cell viability by CellTiter-Glo assay, colony formation, and immunoblotting in DLD-1 cells treated with the indicated doses of Thal SNS 032 (O to Q) or dBET6 (R to T) alone or with tariquidar. Cells were treated for 14 days for colony formation assays and 24 hours for immunoblotting.
Fig. 5. Repurposing dual kinase/MDR1 inhibitors to overcome degrader resistance in cancer cells. (A and B) Drug efflux activity by rhodamine 123 efflux assays in degrader-resistant [dBET-R (A) or Thal-R (B)] A1847 cells after treatment with tariquidar, RAD001, or lapatinib (each 2 μM). Data are means ± SD of three independent experiments. *P ≤ 0.05 by Student’s t test. (C and D) CellTiter-Glo assay for the cell viability of parental, dBET6-R, or Thal-R A1847 cells treated with increasing concentrations of RAD001 (C) or lapatinib (D). Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. GI50 values were determined with Prism software. (E to I) Immunoblot analysis of degrader targets in parental (E), dBET6-R (F and G), and Thal-R (H and I) A1847 cells treated with increasing concentrations of RAD001 or lapatinib for 4 hours. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value of dBET6 for BRD4 reduction (G) or of Thal SNS 032 for CDK9 reduction (I) determined with Prism. (J) Immunoblotting for cleaved PARP in dBET6-R or Thal-R A1847 cells treated with RAD001, lapatinib, or tariquidar (each 2 μM) for 24 hours. Blots are representative of three independent blots. (K to N) Immunoblotting for BRD4 in DLD-1 cells treated with increasing doses of dBET6 alone or in combination with either RAD001 or lapatinib [each 2 μM (K and L)] or KU-0063794 or afatinib [each 2 μM (M and N)] for 4 hours. Blots are representative of three independent experiments and, in (L), are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value for BRD4 reduction (L) determined in Prism. (O) Colony formation by DLD-1 cells treated with DMSO, dBET6 (0.1 μM), lapatinib (2 μM), afatinib (2 μM), RAD001 (2 μM), KU-0063794 (2 μM), or the combination of inhibitor and dBET6 for 14 days. Images representative of three independent assays. (P and Q) Immunoblotting for CDK9 in DLD-1 cells treated with increasing doses of Thal SNS 032 and/or RAD001 (2 μM) or lapatinib (2 μM) for 4 hours. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value for CDK9 reduction determined with Prism (Q). (R) Colony formation in DLD-1 cells treated with DMSO, Thal SNS 032 (0.5 μM), lapatinib (2 μM), and/or RAD001 (2 μM) as indicated for 14 days.
Fig. 6. Combining MEK1/2 degraders with lapatinib synergistically kills MDR1-overexpressing KRAS-mutant CRC cells and tumors. (A and B) ABCB1 expression in KRAS-mutant CRC cell lines from cBioPortal (30) (A) and MDR1 abundance in select KRAS-mutant CRC cell lines (B). (C) Cell viability assessed by CellTiter-Glo in CRC cells treated with increasing doses of MS432 for 5 days, analyzed as % of DMSO control. GI50 value determined with Prism software. (D) Colony formation by CRC cells 14 days after treatment with 1 μM MS432. (E) MEK1/2 protein levels assessed by immunoblot in CRC lines SKCO1 (low MDR1) or LS513 (high MDR1) treated with increasing doses of MS432 for 4 hours. (F) Rhodamine 123 efflux in LS513 cells treated with DMSO, 2 μM tariquidar, or 2 μM lapatinib. (G and H) Immunoblotting analysis in LS513 cells treated with increasing doses of MS432 alone or in combination with tariquidar (0.1 μM) or lapatinib (5 μM) for 24 hours. DC50 value for MEK1 levels determined with Prism. (I) Immunoblotting in LS513 cells treated with DMSO, PD0325901 (0.01 μM), lapatinib (5 μM), or the combination for 48 hours. (J and K) Immunoblotting in LS513 cells treated either with DMSO, MS432 (1 μM), tariquidar (0.1 μM) (J), or lapatinib (5 μM) (K), alone or in combination. (L) Bliss synergy scores determined from cell viability assays (CellTiter-Glo) in LS513 cells treated with increasing concentrations of MS432, lapatinib, or the combination. (M and N) Colony formation by LS513 cells (M) and others (N) treated with DMSO, lapatinib (2 μM), MS432 (1 μM), or the combination for 14 days. (O and P) Immunoblotting in LS513 cells treated with increasing doses of MS934 alone (O) or combined with lapatinib (5 μM) (P) for 24 hours. (Q and R) Tumor volume of LS513 xenografts (Q) and the body weights of the tumor-bearing nude mice (R) treated with vehicle, MS934 (50 mg/kg), lapatinib (100 mg/kg), or the combination. n = 5 mice per treatment group. In (A) to (R), blots and images are representative of three independent experiments, and quantified data are means ± SD [SEM in (Q) and (R)] of three independent experiments; ***P ≤ 0.001 by Student’s t test.
Fig. 7. Lapatinib treatment improves KRASG12C degrader therapies in MDR1-overexpressing CRC cell lines. (A and B) Colony formation by SW1463 (A) or SW837 (B) cells treated with DMSO, LC-2 (1 μM), or MRTX849 (1 μM) for 14 days. Images representative of three independent assays. (C to E) Immunoblotting in SW1463 cells (C and D) and SW837 cells (E) treated with DMSO, LC-2 (1 μM), tariquidar (0.1 μM) (C), or lapatinib (5 μM) (D and E) alone or in combination for 48 hours. Blots are representative of three independent experiments. (F and G) Bliss synergy scores based on CellTiter-Glo assay for the cell viability of SW1463 (F) or SW837 (G) cells treated with increasing concentrations of LC-2, lapatinib, or the combination. Data are means of three experiments ± SD. (H and I) Colony formation of SW1463 (H) or SW837 (I) cells treated as indicated (−, DMSO; LC-2, 1 μM; lapatinib, 2 μM; tariquidar, 0.1 μM) for 14 days. Images representative of three independent assays. (J) Rationale for combining lapatinib with MEK1/2 or KRASG12C degraders in MDR1-overexpressing CRC cell lines. Simultaneous blockade of MDR1 and ErbB receptor signaling overcomes degrader resistance and ErbB receptor kinome reprogramming, resulting in sustained inhibition of KRAS effector signaling.
AI enabled Drug Discovery and Development: The Challenges and the Promise
Reporter:Aviva Lev-Ari, PhD, RN
Early Development
Caroline Kovac (the first IBM GM of Life Sciences) is the one who started in silico development of drugs in 2000 using a big db of substances and computer power. She transformed an idea into $2b business. Most of the money was from big pharma. She was asking what is are the new drugs they are planning to develop and provided the four most probable combinations of substances, based on in Silicon work.
Carol Kovac
General Manager, Healthcare and Life Sciences, IBM
from speaker at conference on 2005
Carol Kovac is General Manager of IBM Healthcare and Life Sciences responsible for the strategic direction of IBM′s global healthcare and life sciences business. Kovac leads her team in developing the latest information technology solutions and services, establishing partnerships and overseeing IBM investment within the healthcare, pharmaceutical and life sciences markets. Starting with only two employees as an emerging business unit in the year 2000, Kovac has successfully grown the life sciences business unit into a multi-billion dollar business and one of IBM′s most successful ventures to date with more than 1500 employees worldwide. Kovac′s prior positions include general manager of IBM Life Sciences, vice president of Technical Strategy and Division Operations, and vice president of Services and Solutions. In the latter role, she was instrumental in launching the Computational Biology Center at IBM Research. Kovac sits on the Board of Directors of Research!America and Africa Harvest. She was inducted into the Women in Technology International Hall of Fame in 2002, and in 2004, Fortune magazine named her one of the 50 most powerful women in business. Kovac earned her Ph.D. in chemistry at the University of Southern California.
The use of artificial intelligence in drug discovery, when coupled with new genetic insights and the increase of patient medical data of the last decade, has the potential to bring novel medicines to patients more efficiently and more predictably.
Jack Fuchs, MBA ’91, an adjunct lecturer who teaches “Principled Entrepreneurial Decisions” at Stanford School of Engineering, moderated and explored how clearly articulated principles can guide the direction of technological advancements like AI-enabled drug discovery.
Kim Branson, Global head of AI and machine learning at GSK.
Russ Altman, the Kenneth Fong Professor of Bioengineering, of genetics, of medicine (general medical discipline), of biomedical data science and, by courtesy, of computer science.
Synthetic Biology Software applied to development of Galectins Inhibitors at LPBI Group
Using Structural Computation Models to Predict Productive PROTAC Ternary Complexes
Ternary complex formation is necessary but not sufficient for target protein degradation. In this research, Bai et al. have addressed questions to better understand the rate-limiting steps between ternary complex formation and target protein degradation. They have developed a structure-based computer model approach to predict the efficiency and sites of target protein ubiquitination by CRNB-binding PROTACs. Such models will allow a more complete understanding of PROTAC-directed degradation and allow crafting of increasingly effective and specific PROTACs for therapeutic applications.
Another major feature of this research is that it a result of collaboration between research groups at Amgen, Inc. and Promega Corporation. In the past commercial research laboratories have shied away from collaboration, but the last several years have found researchers more open to collaborative work. This increased collaboration allows scientists to bring their different expertise to a problem or question and speed up discovery. According to Dr. Kristin Riching, Senior Research Scientist at Promega Corporation, “Targeted protein degraders have broken many of the rules that have guided traditional drug development, but it is exciting to see how the collective learnings we gain from their study can aid the advancement of this new class of molecules to the clinic as effective therapeutics.”
The Map of human proteins drawn by artificial intelligence and PROTAC (proteolysis targeting chimeras) Technology for Drug Discovery
Curators: Dr. Stephen J. Williams and Aviva Lev-Ari, PhD, RN
UPDATED on 11/5/2021
Introducing Isomorphic Labs
I believe we are on the cusp of an incredible new era of biological and medical research. Last year DeepMind’s breakthrough AI system AlphaFold2 was recognised as a solution to the 50-year-old grand challenge of protein folding, capable of predicting the 3D structure of a protein directly from its amino acid sequence to atomic-level accuracy. This has been a watershed moment for computational and AI methods for biology. Building on this advance, today, I’m thrilled to announce the creation of a new Alphabet company – Isomorphic Labs – a commercial venture with the mission to reimagine the entire drug discovery process from the ground up with an AI-first approach and, ultimately, to model and understand some of the fundamental mechanisms of life.
For over a decade DeepMind has been in the vanguard of advancing the state-of-the-art in AI, often using games as a proving ground for developing general purpose learning systems, like AlphaGo, our program that beat the world champion at the complex game of Go. We are at an exciting moment in history now where these techniques and methods are becoming powerful and sophisticated enough to be applied to real-world problems including scientific discovery itself. One of the most important applications of AI that I can think of is in the field of biological and medical research, and it is an area I have been passionate about addressing for many years. Now the time is right to push this forward at pace, and with the dedicated focus and resources that Isomorphic Labs will bring.
An AI-first approach to drug discovery and biology The pandemic has brought to the fore the vital work that brilliant scientists and clinicians do every day to understand and combat disease. We believe that the foundational use of cutting edge computational and AI methods can help scientists take their work to the next level, and massively accelerate the drug discovery process. AI methods will increasingly be used not just for analysing data, but to also build powerful predictive and generative models of complex biological phenomena. AlphaFold2 is an important first proof point of this, but there is so much more to come. At its most fundamental level, I think biology can be thought of as an information processing system, albeit an extraordinarily complex and dynamic one. Taking this perspective implies there may be a common underlying structure between biology and information science – an isomorphic mapping between the two – hence the name of the company. Biology is likely far too complex and messy to ever be encapsulated as a simple set of neat mathematical equations. But just as mathematics turned out to be the right description language for physics, biology may turn out to be the perfect type of regime for the application of AI. What’s next for Isomorphic Labs This is just the beginning of what we hope will become a radical new approach to drug discovery, and I’m incredibly excited to get this ambitious new commercial venture off the ground and to partner with pharmaceutical and biomedical companies. I will serve as CEO for Isomorphic’s initial phase, while remaining as DeepMind CEO, partially to help facilitate collaboration between the two companies where relevant, and to set out the strategy, vision and culture of the new company. This will of course include the building of a world-class multidisciplinary team, with deep expertise in areas such as AI, biology, medicinal chemistry, biophysics, and engineering, brought together in a highly collaborative and innovative environment. (We are hiring!) As pioneers in the emerging field of ‘digital biology’, we look forward to helping usher in an amazingly productive new age of biomedical breakthroughs. Isomorphic’s mission could not be a more important one: to use AI to accelerate drug discovery, and ultimately, find cures for some of humanity’s most devastating diseases.
AI research lab DeepMind has created the most comprehensive map of human proteins to date using artificial intelligence. The company, a subsidiary of Google-parent Alphabet, is releasing the data for free, with some scientists comparing the potential impact of the work to that of the Human Genome Project, an international effort to map every human gene.
Proteins are long, complex molecules that perform numerous tasks in the body, from building tissue to fighting disease. Their purpose is dictated by their structure, which folds like origami into complex and irregular shapes. Understanding how a protein folds helps explain its function, which in turn helps scientists with a range of tasks — from pursuing fundamental research on how the body works, to designing new medicines and treatments. “the culmination of the entire 10-year-plus lifetime of DeepMind” Previously, determining the structure of a protein relied on expensive and time-consuming experiments. But last year DeepMind showed it can produce accurate predictions of a protein’s structure using AI software called AlphaFold. Now, the company is releasing hundreds of thousands of predictions made by the program to the public. “I see this as the culmination of the entire 10-year-plus lifetime of DeepMind,” company CEO and co-founder Demis Hassabis told The Verge. “From the beginning, this is what we set out to do: to make breakthroughs in AI, test that on games like Go and Atari, [and] apply that to real-world problems, to see if we can accelerate scientific breakthroughs and use those to benefit humanity.”
Two examples of protein structures predicted by AlphaFold (in blue) compared with experimental results (in green). Image: DeepMind
There are currently around 180,000 protein structures available in the public domain, each produced by experimental methods and accessible through the Protein Data Bank. DeepMind is releasing predictions for the structure of some 350,000 proteins across 20 different organisms, including animals like mice and fruit flies, and bacteria like E. coli. (There is some overlap between DeepMind’s data and pre-existing protein structures, but exactly how much is difficult to quantify because of the nature of the models.) Most significantly, the release includes predictions for 98 percent of all human proteins, around 20,000 different structures, which are collectively known as the human proteome. It isn’t the first public dataset of human proteins, but it is the most comprehensive and accurate.
If they want, scientists can download the entire human proteome for themselves, says AlphaFold’s technical lead John Jumper. “There is a HumanProteome.zip effectively, I think it’s about 50 gigabytes in size,” Jumper tells The Verge. “You can put it on a flash drive if you want, though it wouldn’t do you much good without a computer for analysis!” “anyone can use it for anything” After launching this first tranche of data, DeepMind plans to keep adding to the store of proteins, which will be maintained by Europe’s flagship life sciences lab, the European Molecular Biology Laboratory (EMBL). By the end of the year, DeepMind hopes to release predictions for 100 million protein structures, a dataset that will be “transformative for our understanding of how life works,” according to Edith Heard, director general of the EMBL. The data will be free in perpetuity for both scientific and commercial researchers, says Hassabis. “Anyone can use it for anything,” the DeepMind CEO noted at a press briefing. “They just need to credit the people involved in the citation.” The benefits of protein folding
Understanding a protein’s structure is useful for scientists across a range of fields. The information can help design new medicines, synthesize novel enzymes that break down waste materials, and create crops that are resistant to viruses or extreme weather. Already, DeepMind’s protein predictions are being used for medical research, including studying the workings of SARS-CoV-2, the virus that causes COVID-19. “it will definitely have a huge impact for the scientific community” New data will speed these efforts, but scientists note it will still take a lot of time to turn this information into real-world results. “I don’t think it’s going to be something that changes the way patients are treated within the year, but it will definitely have a huge impact for the scientific community,” Marcelo C. Sousa, a professor at the University of Colorado’s biochemistry department, told The Verge. Scientists will have to get used to having such information at their fingertips, says DeepMind senior research scientist Kathryn Tunyasuvunakool. “As a biologist, I can confirm we have no playbook for looking at even 20,000 structures, so this [amount of data] is hugely unexpected,” Tunyasuvunakool told The Verge. “To be analyzing hundreds of thousands of structures — it’s crazy.”
Notably, though, DeepMind’s software produces predictions of protein structures rather than experimentally determined models, which means that in some cases further work will be needed to verify the structure. DeepMind says it spent a lot of time building accuracy metrics into its AlphaFold software, which ranks how confident it is for each prediction.
Example protein structures predicted by AlphaFold. Image: DeepMind Predictions of protein structures are still hugely useful, though. Determining a protein’s structure through experimental methods is expensive, time-consuming, and relies on a lot of trial and error. That means even a low-confidence prediction can save scientists years of work by pointing them in the right direction for research. Helen Walden, a professor of structural biology at the University of Glasgow, tells The Verge that DeepMind’s data will “significantly ease” research bottlenecks, but that “the laborious, resource-draining work of doing the biochemistry and biological evaluation of, for example, drug functions” will remain. Sousa, who has previously used data from AlphaFold in his work, says for scientists the impact will be felt immediately. “In our collaboration we had with DeepMind, we had a dataset with a protein sample we’d had for 10 years, and we’d never got to the point of developing a model that fit,” he says. “DeepMind agreed to provide us with a structure, and they were able to solve the problem in 15 minutes after we’d been sitting on it for 10 years.”
Why protein folding is so difficult
Proteins are constructed from chains of amino acids, which come in 20 different varieties in the human body. As any individual protein can be comprised of hundreds of individual amino acids, each of which can fold and twist in different directions, it means a molecule’s final structure has an incredibly large number of possible configurations. One estimate is that the typical protein can be folded in 10^300 ways — that’s a 1 followed by 300 zeroes.
Protein folding has been a “grand challenge” of biology for decades
Because proteins are too small to examine with microscopes, scientists have had to indirectly determine their structure using expensive and complicated methods like nuclear magnetic resonance and X-ray crystallography. The idea of determining the structure of a protein simply by reading a list of its constituent amino acids has been long theorized but difficult to achieve, leading many to describe it as a “grand challenge” of biology. In recent years, though, computational methods — particularly those using artificial intelligence — have suggested such analysis is possible. With these techniques, AI systems are trained on datasets of known protein structures and use this information to create their own predictions.
DeepMind’s AlphaFold software has significantly increased the accuracy of computational protein-folding, as shown by its performance in the CASP competition. Image: DeepMind Many groups have been working on this problem for years, but DeepMind’s deep bench of AI talent and access to computing resources allowed it to accelerate progress dramatically. Last year, the company competed in an international protein-folding competition known as CASP and blew away the competition. Its results were so accurate that computational biologist John Moult, one of CASP’s co-founders, said that “in some sense the problem [of protein folding] is solved.”
DeepMind’s AlphaFold program has been upgraded since last year’s CASP competition and is now 16 times faster. “We can fold an average protein in a matter of minutes, most cases seconds,” says Hassabis.
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The company also released the underlying code for AlphaFold last week as open-source, allowing others to build on its work in the future.
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Liam McGuffin, a professor at Reading University who developed some of the UK’s leading protein-folding software, praised the technical brilliance of AlphaFold, but also noted that the program’s success relied on decades of prior research and public data. “DeepMind has vast resources to keep this database up to date and they are better placed to do this than any single academic group,” McGuffin told The Verge. “I think academics would have got there in the end, but it would have been slower because we’re not as well resourced.”
Why does DeepMind care?
Many scientists The Verge spoke to noted the generosity of DeepMind in releasing this data for free. After all, the lab is owned by Google-parent Alphabet, which has been pouring huge amounts of resources into commercial healthcare projects. DeepMind itself loses a lot of money each year, and there have been numerousreportsof tensions between the company and its parent firm over issues like research autonomy and commercial viability.
Hassabis, though, tells The Verge that the company always planned to make this information freely available, and that doing so is a fulfillment of DeepMind’s founding ethos. He stresses that DeepMind’s work is used in lots of places at Google — “almost anything you use, there’s some of our technology that’s part of that under the hood” — but that the company’s primary goal has always been fundamental research. “There’s many ways value can be attained.”
“The agreement when we got acquired is that we are here primarily to advance the state of AGI and AI technologies and then use that to accelerate scientific breakthroughs,” says Hassabis. “[Alphabet] has plenty of divisions focused on making money,” he adds, noting that DeepMind’s focus on research “brings all sorts of benefits, in terms of prestige and goodwill for the scientific community. There’s many ways value can be attained.” Hassabis predicts that AlphaFold is a sign of things to come — a project that shows the huge potential of artificial intelligence to handle messy problems like human biology.
“I think we’re at a really exciting moment,” he says. “In the next decade, we, and others in the AI field, are hoping to produce amazing breakthroughs that will genuinely accelerate solutions to the really big problems we have here on Earth.”
Abstract PROTACs-induced targeted protein degradation has emerged as a novel therapeutic strategy in drug development and attracted the favor of academic institutions, large pharmaceutical enterprises (e.g., AstraZeneca, Bayer, Novartis, Amgen, Pfizer, GlaxoSmithKline, Merck, and Boehringer Ingelheim, etc.), and biotechnology companies. PROTACs opened a new chapter for novel drug development. However, any new technology will face many new problems and challenges. Perspectives on the potential opportunities and challenges of PROTACs will contribute to the research and development of new protein degradation drugs and degrader tools.
Although PROTAC technology has a bright future in drug development, it also has many challenges as follows: (1) Until now, there is only one example of PROTAC reported for an “undruggable” target; (18) more cases are needed to prove the advantages of PROTAC in “undruggable” targets in the future. (2) “Molecular glue”, existing in nature, represents the mechanism of stabilized protein–protein interactions through small molecule modulators of E3 ligases. For instance, auxin, the plant hormone, binds to the ligase SCF-TIR1 to drive recruitment of Aux/IAA proteins and subsequently triggers its degradation. In addition, some small molecules that induce targeted protein degradation through “molecular glue” mode of action have been reported. (21,22) Furthermore, it has been recently reported that some PROTACs may actually achieve target protein degradation via a mechanism that includes “molecular glue” or via “molecular glue” alone. (23) How to distinguish between these two mechanisms and how to combine them to work together is one of the challenges for future research. (3) Since PROTAC acts in a catalytic mode, traditional methods cannot accurately evaluate the pharmacokinetics (PK) and pharmacodynamics (PD) properties of PROTACs. Thus, more studies are urgently needed to establish PK and PD evaluation systems for PROTACs. (4) How to quickly and effectively screen for target protein ligands that can be used in PROTACs, especially those targeting protein–protein interactions, is another challenge. (5) How to understand the degradation activity, selectivity, and possible off-target effects (based on different targets, different cell lines, and different animal models) and how to rationally design PROTACs etc. are still unclear. (6) The human genome encodes more than 600 E3 ubiquitin ligases. However, there are only very few E3 ligases (VHL, CRBN, cIAPs, and MDM2) used in the design of PROTACs. How to expand E3 ubiquitin ligase scope is another challenge faced in this area.
PROTAC technology is rapidly developing, and with the joint efforts of the vast number of scientists in both academia and industry, these problems shall be solved in the near future.
PROTACs have opened a new chapter for the development of new drugs and novel chemical knockdown tools and brought unprecedented opportunities to the industry and academia, which are mainly reflected in the following aspects: (1) Overcoming drug resistance of cancer. In addition to traditional chemotherapy, kinase inhibitors have been developing rapidly in the past 20 years. (12) Although kinase inhibitors are very effective in cancer therapy, patients often develop drug resistance and disease recurrence, consequently. PROTACs showed greater advantages in drug resistant cancers through degrading the whole target protein. For example, ARCC-4 targeting androgen receptor could overcome enzalutamide-resistant prostate cancer (13) and L18I targeting BTK could overcome C481S mutation. (14) (2) Eliminating both the enzymatic and nonenzymatic functions of kinase. Traditional small molecule inhibitors usually inhibit the enzymatic activity of the target, while PROTACs affect not only the enzymatic activity of the protein but also nonenzymatic activity by degrading the entire protein. For example, FAK possesses the kinase dependent enzymatic functions and kinase independent scaffold functions, but regulating the kinase activity does not successfully inhibit all FAK function. In 2018, a highly effective and selective FAK PROTAC reported by Craig M. Crews’ group showed a far superior activity to clinical candidate drug in cell migration and invasion. (15) Therefore, PROTAC can expand the druggable space of the existing targets and regulate proteins that are difficult to control by traditional small molecule inhibitors. (3) Degrade the “undruggable” protein target. At present, only 20–25% of the known protein targets (include kinases, G protein-coupled receptors (GPCRs), nuclear hormone receptors, and iron channels) can be targeted by using conventional drug discovery technologies. (16,17) The proteins that lack catalytic activity and/or have catalytic independent functions are still regarded as “undruggable” targets. The involvement of Signal Transducer and Activator of Transcription 3 (STAT3) in the multiple signaling pathway makes it an attractive therapeutic target; however, the lack of an obviously druggable site on the surface of STAT3 limited the development of STAT3 inhibitors. Thus, there are still no effective drugs directly targeting STAT3 approved by the Food and Drug Administration (FDA). In November 2019, Shaomeng Wang’s group first reported a potent PROTAC targeting STAT3 with potent biological activities in vitro and in vivo. (18) This successful case confirms the key potential of PROTAC technology, especially in the field of “undruggable” targets, such as K-Ras, a tricky tumor target activated by multiple mutations as G12A, G12C, G12D, G12S, G12 V, G13C, and G13D in the clinic. (19) (4) Fast and reversible chemical knockdown strategy in vivo. Traditional genetic protein knockout technologies, zinc-finger nuclease (ZFN), transcription activator-like effector nuclease (TALEN), or CRISPR-Cas9, usually have a long cycle, irreversible mode of action, and high cost, which brings a lot of inconvenience for research, especially in nonhuman primates. In addition, these genetic animal models sometimes produce phenotypic misunderstanding due to potential gene compensation or gene mutation. More importantly, the traditional genetic method cannot be used to study the function of embryonic-lethal genes in vivo. Unlike DNA-based protein knockout technology, PROTACs knock down target proteins directly, rather than acting at the genome level, and are suitable for the functional study of embryonic-lethal proteins in adult organisms. In addition, PROTACs provide exquisite temporal control, allowing the knockdown of a target protein at specific time points and enabling the recovery of the target protein after withdrawal of drug treatment. As a new, rapid and reversible chemical knockdown method, PROTAC can be used as an effective supplement to the existing genetic tools. (20)
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