Susan Haigney

Tablet, hands or doctor with human body hologram for futuristic research, 3d ai analysis or hospital innovation. Life insurance, medical or man with virtual holographic anatomy for digital healthcare | Image Credit: © 

Pharmaceutical companies face a variety of challenges, such as the "patent cliff" and the difficulty of discovering new "blockbuster" drugs, when researching and developing potential new products (1). As part of the drug development toolbox, pharma companies are integrating AI and machine learning (ML) not only during discovery and development, but across the entire lifecycle of a drug (1,2). This technological shift is not merely about automation but reimagines how therapies are discovered, tested, and brought to market (1, 3).

A report from the Capgemini Research Institute details how the industry is moving to AI to reduce costs and clinical failure rates (4). A survey of 500 senior executives across eight countries found that a majority (82%) believe AI will fundamentally transform biopharma R&D, with 63% saying that a failure to scale AI will leave companies behind when it comes to innovation and market relevance (4). They also anticipate that in the next decade, most new molecular entities will be created using AI-driven platforms.

How is AI accelerating early-stage discovery and solubility?

Poor solubility of new chemical entities is consistently a challenge in drug development, with an estimated 70–90% of drug candidates categorized as poorly soluble (5, 6). Traditionally, identifying the right formulation for these "brick dust" or "greaseball" molecules required extensive and expensive empirical trial-and-error (5,6). However, 

 using AI and ML is now being leveraged to predict physicochemical properties and guide early-stage decision making (5,6). Researchers can identify optimal solubilization methods and suitable excipients by utilizing tools like quantum mechanical calculations and molecular dynamics simulations (5). This "ultra-material-sparing" approach significantly reduces API consumption and saves money in research costs (5). A notable example is the evaluation of the compound CVN424, for which predictive modeling guided the selection of spray-dried formulations, accelerating the overall development timeline (6).

How are digital twins improving personalized clinical evaluations?

The use of digital twins in preclinical evaluation is revolutionizing how drugs are tested on human organs (7). For example, by using an

lung perfusion system, researchers can keep human lungs alive outside the body to collect "clean" multimodal data. Machine learning models then use these data to create a personalized digital control arm for every organ being treated.

This approach allows for a direct comparison between observed treatment effects and a digital twin-generated, "untreated" outcome within the same organ. By reducing the reliance on large control groups and traditional animal models, digital twins may reduce study sizes and accelerate clinical trials (7).

How are regulatory workflows and market access streamlined?

New regulations in the European Union requiring complex joint clinical assessments has added to the burden of regulatory compliance and health technology assessments. Generative AI (GenAI) is being utilized to work with the raw data to complete these submissions (8) by automating the creation of clinical evidence summaries, reducing the time spent on initial dossier drafting by approximately 40% in some cases.

Beyond documentation, agentic AI can automate labor-intensive processes in trial master file management, intaking and classifying documents with "human-in-the-loop" checkpoints for quality control (9).

Domain-specific models and secure collaboration

While general-purpose AI models are proficient in language, they often lack the depth required for the highly regulated pharmaceutical market (9). To combat this, domain-specific language models can be trained on proprietary enterprise documentation, such as batch records and validated procedures to support high-stakes decisions regarding drug manufacturing and clinical protocols (10).

To improve communication between regulators and drug developers, secure cloud environments, like the PRISM project, are enabling both parties to work on the same documents in real-time, using AI agent-like functions to accelerate the regulatory process and ensure that safety and efficacy are addressed long before a product reaches the patient (1,2).

What AI tools are entering the drug development space?

In recent years, drug developers have put a lot of time, money, and effort into oncology. In January 2026, SOPHiA GENETICS, a company working in AI-driven precision medicine, announced a collaboration with MD Anderson Cancer Center, which will utilize SOPHiA GENETIC’s AI-powered analytics platform. The organizations will launch research and development programs and co-develope a next-generation sequencing oncology test to translate complex multimodal data (11).

Also in January, the AI-drug discovery company Oxford Drug Design announced that it has successfully completed 

 validation of a novel therapeutic approach targeting multiple tumor types in the development of a potential first-in-class cancer therapy using its GenAI platform (12). “In studies using a genetically engineered mouse model that replicates the earliest mutational events in colorectal cancer, Oxford Drug Design’s lead compound demonstrated statistically significant anti-tumor activity with efficacy comparable to that of rapamycin–a benchmark therapy– while showing no detectable signs of toxicity,” the company explained in a press release (12).

Iktos, a company that applies AI and robotics to drug discovery, entered into a multi-target collaboration agreement with the pharmaceutical company Servier with the goal of leveraging Iktos’ AI-orchestrated discovery platform to accelerate the design and optimization of novel small-molecule therapeutics in oncology and neurology. Iktos will apply its generative AI and AI-orchestrated robotics platform to design, synthesize, and optimize small molecules for multiple undisclosed targets, which will then be evaluated and potentially selected by Servier for preclinical and clinical development (13).

Experts stress that AI and other digital technologies are force multipliers, not replacements for human expertise (7,9). Successful integration requires a "digitally fluent" workforce who can supervise automated systems and interpret AI-generated impact assessments (3). By automating administrative burdens, AI allows scientists and regulatory experts to return to the core of their work: scientific reasoning and clinical judgment (2, 8).

Responsible deployment of AI and machine learning creates a more efficient and equitable path to innovation, shortening the time between the discovery of a molecule and the treatment of a patient (8).

Cole, C. Global Collaboration and Technological Acceleration to Evolve Drug Innovation. 

Cole, C. Harnessing Data and Secure Cloud Environments for Global Pharma Solutions. 

Cole, C. Orchestrating the Pharmaceutical Future: Living Decision Engines and AI Integration. 

Capgemini. Smart Bet, Only Option, or Both?: Biopharma R&D turns to AI. 

https://www.capgemini.com/insights/research-library/how-ai-will-transform-life-sciences-r-and-d/

Mirasol, F.; Lavery, P. Leveraging AI/ML to Reduce Risk in Drug Development: Part One. 

Cole, C. Using AI and Molecular Dynamics to Overcome the Poor Solubility Challenge. 

Cole, C.; Mirasol, F. Achieving a Personalized Digital Control Arm for Preclinical Drug Evaluation. 

Dhas, A. Accelerating HTA Readiness with Generative AI. 

Medable. Medable Launches New AI Agent for Automating Clinical Trial Document Management; Presenting at JPM Health. Press Release. Jan. 6, 2026.

Nair, J. Why Pharma’s AI Agents Need Smaller, Domain-Specific Models First. 

SOPHiA GENETICS. SOPHiA GENETICS and MD Anderson Announce Strategic Collaboration to Accelerate AI-Driven Precision Oncology. Press Release. Jan. 7, 2026.

Oxford Drug Design. Oxford Drug Design Announces Further 

 Validation of Novel Oncology Therapeutic Mechanism. Press Release. Jan. 12, 2026.

Iktos. Iktos Enters Strategic €1B+ Multi-Target AI Partnership with Servier to Advance Drug Discovery in Oncology and Neurology. Press Release. Jan. 8, 2026.

Articles

Pharmaceutical companies are increasingly integrating AI and machine learning across the drug lifecycle to address challenges like the "patent cliff" and drug discovery difficulties. AI is transforming biopharma R&D by reducing costs and clinical failure rates, with a significant impact anticipated in the next decade. AI-driven tools are enhancing early-stage discovery, solubility, and personalized clinical evaluations. Regulatory workflows are streamlined using generative AI, while domain-specific models improve decision-making. Collaborations in AI-driven precision medicine and drug discovery are advancing oncology and neurology therapeutics, emphasizing the importance of human expertise in a digital ecosystem.

AI and machine learning are helping pharmaceutical scientists more efficiently develop innovative and novel treatments for a range of disease areas.

Integrating AI and Machine Learning in Drug Discovery and Development

AI is being utilized to prioritize clinical trials by identifying areas of significant unmet medical need, such as Alzheimer’s disease, ensuring resources are directed where they are most required rather than toward well-treated conditions. A digital representation of a patient comprising genomic data and therapy history may be used to facilitate precision prescription, helping clinicians select the optimal therapy from a pipeline of candidates based on an individual's unique biological differences, according to Michelle Longmire, CEO and Co-Founder, Medable. Beyond the lab, AI can streamline the "final mile" of medicine by educating physicians on newly approved drugs directly within patient records, bypassing the need for doctors to manually track every new approval.

The introduction of agentic AI aims to solve the inefficiency in clinical trials, where currently 80–90% of processes are manual. By deploying autonomous agents to handle tactical data collection and "heavy lifting," AI removes the administrative overhead that currently occupies half of a professional's day. This shift allows human experts to focus on strategic work, such as optimizing site openings or trial enrollment. Longmire predicts that by 2030, while technology will consume over 60% of budgets, the overall cost of healthcare will decrease.

, being held in San Francisco from January 12–15, to find out more about how AI and machine learning are improving the use of patient data to enhance treatment options.

PharmTech: How can AI/machine learning be used to predict which therapies will best meet treatment needs, especially for rare diseases or cancer treatments?

[Approaching] the problem from post-discovery and looking at the in-human trials, the most important thing that we really look at is how can you accelerate the inhuman testing part? When we think about unmet needs, we're looking at it from [for example] you've got 9000 candidates or a number of different treatments you want to try and [put through] clinical trials, where is the real unmet need? So that would drive the prioritization in the resourcing and timeline of the clinical trials. [If] you have 10 or 20 different candidates, and one is for psoriasis, and one's for Alzheimer's disease, I think, from our perspective, there's already great therapies for all psoriasis. So, let’s focus on where there really is an unmet medical need, and target company resources towards that need first.

How are AI and ML platforms being utilized to match the patient to the treatment?

We know that certain people respond to certain therapies better than others. One of the things that we've really been advocating for is something we call the digitome, which is a digital representation of a patient, and this enables us to get more precise, better data. This would include genomics data past therapies and failed therapies, in some cases, even looking at the genomics of drug processing. One of the areas that we're really excited about for machine learning and AI is, how do you do precision prescription? Let's say AI discovery unlocks the pipeline, and you've got 10 different therapies for a disease. What's the best one for the patient in front of me? That's a really important role for AI. And I think it's going to be exciting as more people have high-fidelity data about what makes them different as humans versus what makes us all similar. Clinical trials are good at solving for the common denominator in humans which is key because, of course, humans are more alike than different. But when prescribers can turn to many options, it is better to take a precision prescribing approach to decide which of these different therapeutic options is best for an individual person based on their differences.

What other uses for AI or ML do you see on the horizon?

Generally in healthcare, there's a big opportunity to use AI to do some of the initial triage, even diagnosing and prescribing as described earlier. I am a trained dermatologist in a relatively small pool of about 8000 dermatologists in the United States, which means there is often a two- to three-month wait time for patients to see one of us. Way back in 2013, Medable had a patent on using machine learning and computer vision for visual diagnosis. We have the data and publications galore that show this is safe and effective. It's just not widely being used. As people become more comfortable with this and we have reimbursement models, then we will be really able to target these unmet needs. AI could even be leveraged for initial triage, diagnosis, and prescribing in specialty care areas.

How do you think these platforms can prevent the bottleneck that happens with drug discovery, drug formulation, or just getting a drug to market?

One key way to accelerate commercialization is by educating physicians about new therapies. Medable and the industry invest a lot of time and money in driving new therapies to approval, but honestly, most doctors aren't even aware of cutting edge therapies available. There's a big opportunity to use AI to help identify the latest and greatest drug for each individual patient. And take some of that final mile work [of] “hey, have to learn the last 54 drugs that were approved last year, or the five that relate to my specialty,” off of a doctor’s plate and streamline that for physicians. It empowers them to help their patients sooner rather than waiting to hear about some new breakthrough at the next the big medical conference in the year.

What are you presenting at the JP Morgan Healthcare Conference this year?

We're really focused on the fact that 80–90% of clinical trials are manual, and that, in our opinion, this is a big reason why we haven't changed the number of drugs approved in a year, no matter how much technology we throw at this, because you're only really previously looking at 10–20% of where you could apply technology. Now with agentic AI, we can remove that tactical overhead. We can actually do many more complex things with AI that were formerly only able to be done by humans. We've released agents that essentially autonomously do significant parts of the work to enable humans to do more strategic work and remove that manual bottleneck.

How do we end up in a world where there's real autonomy to AI to do a lot of the heavy lifting, and humans can do the more strategic work? Most of the [people] we've spoken with as we've developed the technology, about half of their day, if not more, is spent doing tactical data collection, you know, going to the system, getting this data here, putting it in an Excel sheet. A minority of time I spent looking at that and saying, okay, strategically, what do we do to make this trial enroll faster, to open this site faster, to address the fact that say there aren't enough patients meeting the inclusion exclusion. So, we're using AI to remove that whole tactical overhead. And we envision that, you know, by 2030, probably 60% plus of the budgets will go to technology, but the important part, the overall cost will go down, and humans will play a much more strategic role.

What are regulators like FDA saying about this use of AI?

I think their guidance is at a fairly high level. But the really positive thing is, most of these have a good clinical practice lens, which is just a set of guiding principles. It's not prescriptive. So, there's a fairly strong framework for good clinical practice and being able to show that AI does good clinical practice as well as humans or better.

Michelle Longmire, CEO and Co-Founder, Medable

As the co-founder and chief executive officer of Medable, Dr. Michelle Longmire is mission-driven to accelerate the development of new therapies for disease. A Stanford-trained physician-scientist, Dr. Longmire witnessed firsthand the critical barriers to drug development – including the time and costs associated with clinical trial participation. She founded Medable to pioneer a new category of clinical trial technologies that remove traditional roadblocks to participation and radically accelerate the research process. Medable is now the industry leader in decentralized and direct-to-patient research, with the ability to serve patients in over 120 languages, 60 countries, and across all therapeutic areas. In addition to having raised over $500M in venture capital and driving Medable to an industry-leading position, Dr. Longmire has received recognition as a leading innovator and businesswoman, including being named as one of the 100 most creative people in business by Fast Company.

AI is revolutionizing clinical trials by prioritizing areas with significant unmet medical needs, such as Alzheimer's disease, and optimizing resource allocation. It facilitates precision prescription through digital patient representations, enhancing therapy selection based on individual biological differences. AI also streamlines the "final mile" of medicine by educating physicians on new drugs within patient records. Agentic AI addresses inefficiencies in clinical trials by automating data collection, allowing professionals to focus on strategic tasks. By 2030, technology is expected to dominate budgets, reducing overall healthcare costs while enhancing strategic human roles.

AI and machine learning may be the ideal tools to evaluate patient data and predict ideal treatment options.

The Transformative Potential of AI to Enhance Patient Treatment

Box and bottle of pills on the blue background. Pharmacy mockups for meds presentations, BADs and other kinds of pharmaceutical products. Front view. | Image Credit: ©Pykhtik -stock.adobe.com

Contract packaging organization, Tjoapack, announced on Jan. 12, 2026 that it is adding a oral solid dosage bottle packaging line to its Etten-Leur facility in The Netherlands (1). The new line will streamline operations and increase a range of formats and presentation options and will provide the ability to switch between different packaging configurations on one line.

The new Cremer Uhlmann IBC 50 line automates bottle packaging for any shape of bottle and can fill up to 50 bottles per minute. The line is good manufacturing practice (GMP) compliant and offers flexibility for bottles to be packed into cartons together with a leaflet or booklet and wrapped in plastic using a shrink tunnel.

According to the company, the investment is in response to growth in the pharmaceutical bottle packaging market, demand for oral solid dosage drugs, and requirements for flexible, compliant packaging solutions. The company has been investing in infrastructure and technology to strengthen its service capabilities, including expansion of its cold chain and injectable packaging capabilities across the United States and the Netherlands.

“This investment reflects our continued focus on flexibility and operational excellence,” said Geert Vleugels, general manager of Tjoapack Netherlands, in a press release (1). “By introducing a line that supports multiple packaging configurations, we can better align our services with the diverse needs of our customers while maintaining the highest GMP standards. The flexibility this new line offers, enables us to offer tailored solutions using a single, efficient setup, supporting our customers as their products and requirements evolve.”

What other investments has the company made?

In December 2025, Tjoapack announced an expansion of its packaging services and operational footprint at its Clinton, Tenn. facility (2). The new 170,000-sq.-ft. facility will be completed in early 2027 and will include a GMP suite with packaging, labeling, cold chain, and ambient storage capabilities. It will support high-speed packaging lines for solid dosage bottles, blister packs, vials, and autoinjectors.

“This expansion marks a major step in our strategic goal to enhance our presence in the United States. As a crucial market with considerable growth opportunities, it allows us to serve our existing clients more effectively and attract new ones.” said Dexter Tjoa, CEO of Tjoapack, at the time in a press release (2). “We’ve invested heavily in automating our core processes, not only within packaging lines but throughout our cross-company workflows with customers and material vendors. This allows us to reduce human error and enhance accuracy, speed, and flexibility, which ultimately benefits our clients.”

What will Tjoapack showcase at Pharmapack Europe 2026?

 with be showcasing its packaging solutions at the 

 event in Paris on January 21–22 at Paris Expo Porte de Versailles. The team will be at Stand 4D118 to talk about the company’s capabilities in oral solid dosage packaging, vials and prefilled syringes, primary packaging, secondary packaging, biotech packaging, and unit dose packaging.

Tjoapack. Tjoapack Boosts Bottle Packaging Capabilities at Netherlands Facility. Press Release. Jan. 12, 2026.

Tjoapack. Tjoapack Announces Major US Expansion to Improve its Packaging and Logistics Capabilities. Press Release. Dec. 5, 2025. 

https://www.tjoapack.com/news-events/tjoapack-announces-major-us-expansion-to-improve-its-packaging-and-logistics-capabilities

Tjoapack is enhancing its Etten-Leur facility in the Netherlands with a new oral solid dosage bottle packaging line, which will streamline operations and offer flexible packaging configurations. This investment aligns with the growing demand for pharmaceutical bottle packaging and oral solid dosage drugs. Additionally, Tjoapack is expanding its Clinton, Tennessee facility to include a GMP suite and high-speed packaging lines, furthering its strategic presence in the U.S. market. The company will showcase its diverse packaging solutions at the 2026 Pharmapack Europe event in Paris.

The company is adding a second production line at its Etten-Leur facility in The Netherlands to meet customer needs.

Tjoapack Expands Bottle Packaging at Netherlands Facility

Communication between the manufacturing plant and retail stores. | Image Credit: © Cagkan - © Cagkan - stock.adobe.com

On Jan. 12, 2026, Jubilant Biosys Limited, a wholly owned subsidiary of Jubilant Pharmova Limited, announced at the 

, which is being held in San Francisco from January 12–15, that it is opening a new discovery and preclinical facility at Noida in India (1). The new facility will double the contract research, development and manufacturing organization’s (CRDMO) chemistry capacity and will combine discovery and early-phase scale up capabilities with R7B labs and two pilot plants. This expansion will meet the company’s demand for fee-for-service contracts.

Comprehensive route scouting, process design and optimization, scalable synthesis development, analytical services will be available, including salt screening and polymorph evaluation and seamless technology transfer to pilot plants all from the specially designed campus. 

The new facility offers a fully unified route from discovery to scale-up and will complement the company’s Chemistry Research Innovation Center (CRIC) in Greater Noida [Delhi], will feature the addition of multiple manufacturing lines, and will increase the number of scientists at the company to 1300. The small-molecule hub is designed to handle quantities from hundreds of grams up to 25kg and combines two pilot plant blocks with co-located discovery labs. A 20,000-sq.-ft. state-of-the-art R&D space will include 15 reactors ranging from 20L through 250L, and the facility may be expanded multifold in the future with room to quadrupole capacity.

“We have grown rapidly over the past year, well above the wider market, by expanding our FFS offerings, which enable innovators to advance discovery projects with lower risk,” Giuliano Perfetti, CEO, Jubilant Biosys Limited, said in a press release (1). “With improving funding conditions, we anticipate even higher demand next year, and this new facility doubles our existing capabilities. From a client perspective, we can now provide faster discovery delivery and integrated scale-up, with projects seamlessly transferred to our GMP facilities ready for any IND filing and commercial phases.”

How are other outsourcing providers meeting capacity needs?

A variety of contract development and manufacturing organizations (CDMOs) made moves in 2025 to expand facilities and services to meet market demands. In August 2025, Bora Pharmaceuticals expanded manufacturing and packaging capabilities at its Maple Grove, Minn facility that will include 100,000 square feet of dedicated shell space to streamline high-volume production (2).

In June 2025, CDMO, Piramal Pharma Solutions, broke ground on a new sterile injectables development and manufacturing facility in Lexington, Ky. The dedicated fill/finish facility will have services for all integrated programs and specialize in sterile compounding, liquid filling, and lyophilization for sterile injectable drug products (3). The expansion, which is expected to be completed by late 2027, will accommodate commercial-scale sterile injectable manufacturing with 24,000 additional square feet, plus a new laboratory, a new filling line, specialized capping machine, external vial washer, and two commercial-size lyophilizers.

SK pharmteco announced a $6.1 million investment at its Rancho Cordova, Calif. facility in October that expands its solid-phase peptide synthesis and purification capabilities (4). The company also is planning a $260 million small-molecule and peptide production facility in South Korea (5).

Jubilant Biosys Limited. Jubilant Biosys Doubles Early Chemistry Scale-Up Capacity with New Noida Facility in India. Press Release. Jan. 12, 2026.

Bora Pharmaceuticals. Bora Pharmaceuticals Announces Multi-Year Expansion for Midwest Manufacturing Site, as Upsher-Smith Entity Split is Finalized. Press Release. Aug. 5, 2025. 

https://bora-corp.com/bora-pharmaceuticals-announces-multi-year-expansion-for-midwest-manufacturing-site-as-upsher-smith-entity-split-is-finalized/

Piramal Pharma Solutions Breaks Ground on $90M Expansion Plan

SK pharmteco Boosts Domestic Peptide Scale-Up with Investment in California Facility

SK pharmteco Invests $260 Million to Expand Global Small Molecule and Peptide Production

Jubilant Biosys Limited is expanding its capabilities with a new discovery and preclinical facility in Noida, India, doubling its chemistry capacity. This facility will integrate discovery and early-phase scale-up capabilities, featuring R&D labs and pilot plants, and will increase the company's workforce to 1,300 scientists. The expansion aims to meet growing demand for fee-for-service contracts, offering comprehensive services from discovery to scale-up. Other CDMOs, like Bora Pharmaceuticals and Piramal Pharma Solutions, are also expanding their facilities to meet market demands, enhancing manufacturing and packaging capabilities.

The CRDMO’s new facility will double chemistry capacity for drug discovery research and scale-up projects.

Jubilant Biosys Announces New Facility in India

Personalized Medicine vs. Precision Medicine

, the concept of personalized medicine shifted from a general idea that all people should have personalized care based on their circumstances to how biology can be used to design a drug that works for a specific disease at a specific time.

“Precision medicine really is understanding the data, the biology that drives disease, the initial focus on this was really around in oncology, and if we look at the advancements in oncology over the past 15 years, they've been profound with the use of genetics and genomics to identify biological factors in patients tumors that have driven the development of targeted therapies and immunotherapies that have really transformed the treatment of patients with cancer,” Dr. Carter explains. “Now even deeper information on genetics has allowed us to develop gene therapies and other treatments that are transformative for rare diseases, neurodegenerative diseases, and autoimmune disease.”

Patient access to precision medicine is one of the biggest challenges to their success, according to Dr. Carter. “There's a tremendous amount of progress, but the drugs are, while they're fantastic drugs, they're incredibly expensive, they're quite esoteric in terms of how to use them and for which patients, and we need to really understand,” Dr. Carter says. “And this was where we get really into the precision medicine aspect. We need to both understand the biology of the patient’s disease and how to get patients access to the right drugs at the right time in a financially sustainable way for the system.”

Dr. Carter will be discussing how precision-guided platforms can help pharmaceutical companies manage the costs of developing precision medicines, such as cell and gene therapies, and therefore improve patient access, at the 

 in San Francisco, which is being held from January 12–15.

Dr. Jennifer Levin Carter, founder and CEO, Medzown

Jennifer Levin Carter, MD, MPH, MBA is Founder & CEO of Medzown. Dr. Carter is a globally recognized leader in precision medicine, with a proven track record of building transformative companies at the intersection of data, technology, and patient care. She was the Founder and President of N-of-One, Inc., where she served as CEO from 2008–2012 and later as President and Chief Medical Officer until its acquisition by Qiagen (Market Cap $8B) in 2019. At N-of-One, Dr. Carter led the development of award-winning solutions that continue to deliver novel treatment strategies to hundreds of thousands of cancer patients worldwide.

In 2018, Dr. Carter founded a novel clinical trials company focused on reimagining trial design and access. She served as CEO until its pre-launch acquisition by Integral Health (now Valo Health) in March 2019. These experiences cemented her reputation as an innovator in precision medicine, clinical trial delivery, and patient-centered care models.

Following these ventures, Dr. Carter became a Managing Partner and Venture Partner at Sandbox Industries and Blue Venture Fund, a unique collaboration between BCBS companies, BCBSA, and Sandbox. It was in this role—working closely with BCBS executives—that she gained a deep understanding of the challenges associated with the rising costs of cell and gene therapy. This insight inspired her to launch Medzown, where she continues to address those challenges by building scalable, technology-enabled solutions to improve patient access to advanced therapies.

Dr. Carter is also a seasoned healthcare executive, investor, and board member with expertise spanning healthcare IT and services, digital health and machine learning, genomics, drug development, and the creation of next-generation platforms to improve therapeutic access. She currently serves on the Board of Directors of Synteny.ai, TempraMed, Inc., and Target Cancer Foundation, and is a strategic advisor to numerous venture-backed healthcare and life sciences companies.

Previously, she has held board roles at Oncocyte (NASDAQ: OCX), XSphera Biosciences (Co-Founder), CareMax (NASDAQ: CMAX), DFP Healthcare Acquisitions Corp (NASDAQ: DFPH), HouseWorks, eCaring, and others. She also serves on the Director’s Advisory Board at Smilow New Haven Cancer Center at Yale University, the Board of the Blavatnik Fund at Yale University, and the MedExec Women’s Advisory Board.

Dr. Carter earned a BS in Molecular Biophysics and Biochemistry (Phi Beta Kappa, Summa Cum Laude with distinction) from Yale University, an MD from Harvard Medical School, an MPH from Harvard School of Public Health, and an MBA from the Sloan School of Management at MIT. She is a member of the American Association of Corporate Directors (Advanced Professional Director Certification), National Association of Corporate Directors, Women Corporate Directors, Women Business Leaders of the U.S. Health Care Industry Foundation, and Women in Bio.

Videos

Dr. Jennifer Levin Carter, founder and CEO of Medzown, discusses what makes precision medicine different from personalized medicine and what how challenges faced in this evolving field can be overcome. 

Personalized Medicine Vs. Precision Medicine

The Benefits of an Immune-Directed ADC Strategy 

Traditional autoimmune and inflammatory treatments have historically relied on what experts describe as a "carpet bombing strategy," which provides efficacy but causes significant collateral damage to healthy tissue. According to 

Arthur Tzianabos, CEO, Lifordi Immunotherapeutics

, while steroids are a $10 billion market, patients often cannot tolerate them long-term because they "hit not only the disease, but also a lot of other normal, healthy tissue," leading to numerous side effects. This has prompted an industry-wide shift toward "precise targeting of the immune system" through the use of antibody-drug conjugates (ADCs).

VISTA, according to Tzianabos, is a cell surface protein found primarily in the lymphoid and myeloid systems. VISTA is a particularly effective target because it "very rapidly internalizes inside the cell and drops off whatever it’s bound to" before recycling back to the surface. By using VISTA as a gateway, Lifordi’s lead program delivers a "very powerful steroid" directly to the immune cells. This targeted delivery is designed to "avoid the systemic toxicities" of widespread steroid use while maintaining high potency.

The company is currently in a Phase I trial for a rheumatoid arthritis treatment and has begun receiving data. Their progress is supported by 

, including a $41 million raise with participation from Sanofi Ventures, which followed a $70 million Series A (1). This growth occurs amid a broader biotech upswing in late 2025 and early 2026, a period marked by rising valuations and increased M&A activity.

, which is being held in San Francisco from January 12–15, to discuss its ADC strategy and meet with leaders in the industry (2). Tzianabos notes that the environment in the industry has shifted toward a "period of optimism" that was absent in previous years, positioning the company well as they share progress with investors and pharmaceutical partners.

Lifordi Immunotherapeutics. Lifordi Immunotherapeutics Secures Strategic Investment from Sanofi Ventures and Additional Capital from Existing Investors. Press Release. Nov. 18, 2025. 

https://lifordi.reportablenews.com/pr/lifordi-immunotherapeutics-secures-strategic-investment-from-sanofi-ventures-and-additional-capital-from-existing-investors

JP Morgan. JPM 2026. Accessed Jan 9, 2025. 

Arthur Tzianabos, PhD, president and chief executive officer, Lifordi Immunotherapeutics

Arthur O. Tzianabos, PhD, is president and CEO of Lifordi Immunotherapeutics and a Venture Partner at 5AM Ventures. He has more than 30 years of experience in the biotechnology industry and academia leading teams in the discovery, development, clinical translation and commercialization of new treatments for immunology and rare diseases.

Dr. Tzianabos served as President and CEO of Homology Medicines and later became Chair of the Board prior to its merger with Q32 Bio. Dr. Tzianabos is currently a member of the Board of Directors at Q32 Bio and Chair of the Board of Directors at Stoke Therapeutics. Previously, he was Chair of the Board for Akouos Therapeutics (acquired by Eli Lilly in 2022). He also serves on the Development Board for the University of New Hampshire’s College of Life Sciences and Agriculture. Earlier in his career, Dr. Tzianabos had an active role in the development, approval, and commercial launch of multiple therapies for patients with rare genetic disorders at Shire Pharmaceuticals. He also worked closely with the Business Development and Corporate Venture functions to invest in and acquire new companies and technologies to build Shire’s pipeline.

Dr. Tzianabos is trained as an immunologist and was an Associate Professor of Medicine at Harvard Medical School where he maintained laboratories at the Channing Laboratory, Brigham and Women’s Hospital and the Department of Microbiology and Molecular Genetics at Harvard Medical School. He has published more than 80 scientific papers, reviews, book chapters and patents. Dr. Tzianabos holds a PhD in Microbiology from the University of New Hampshire and a B.S. in Biology from Boston College.

Arthur Tzianabos, CEO, Lifordi Immunotherapeutics, spoke with PharmTech about the company’s immune-directed antibody-drug conjugate (ADC) strategy, the benefits of VISTA-targeted ADCs in drug delivery, and Lifordi’s plans at the JP Morgan Healthcare Conference. 