Digital Transformation in Pharma Manufacturing

Patent Cliff Deals, Tariff Pressures, and the In Vivo Cell Therapy Bet

Behind the Headlines, Episode 23

ICH Q12 and Post-Approval Changes

Speed, Flexibility Top Large-Molecule Manufacturing Trends

Drug Digest July 2025

Key Insights from Industry Survey Results

Bio/Pharma's Tariff Response

Feliza Mirasol is the science editor for 

Lonza’s Joe Garrity and Jerry Jiang discuss the importance of not only automating CGT manufacturing, but also standardizing across processes.

The Need for Automated and Standardized CGT Manufacturing (BIO 2024)

While cell and gene therapy (CGT) manufacturing must remain flexible out of necessity, it is also important to standardize processes at an industry level while establishing aseptic-friendly automated operations. Standardization, in particular, is important from a scaling perspective, says Joe Garrity, senior director and head of Autologous Cell Therapy, Lonza.

During BIO 2024, Garrity pointed out the many challenges incurred on the cell therapy side. “It stems from supply chain to operations to clinical sites. There's just so much that needs to go into, specifically, autologous cell therapies, with the batch quantities going into the hundreds and thousands that we're seeing from some of [the] large drug developers.” Thus, he says, standardizing the manufacturing process allows for robustness and process control across the board.

Garrity also notes, however, that even with standardization, “it's not a one size fits all”. Instead, he says, “[much of the time,] it's a little bit of a one size fits most, and you're going to have to be relatively variable, but in the end, the overall standardization of the manufacturing process and the intent of that remains the same because it's better control at scale. Once you find something that really funnels that process robustness and that scalability, you … stick with it so it's reproducible time and time again.”

In discussing whether it’s possible to have manufacturing processes that are both standardized and flexible, Jerry Jiang, clinical application specialist, Personalized Medicine, Cell and Gene Therapy, Lonza, says, “Definitely. One of the things that we really have to start standardizing is the release criteria and the quality of the cells that are being put into the patients. [The] material that comes in is going to be different, but standardizing what we expect the cells to do and behave and what they look like is going to be a huge part of what the standardization process needs to overcome right now.” However, flexibility remains in the details. “[T]he standardization is the same, but the flexibility of the process allows these different companies to optimize the process with their ‘secret sauce’ that will really differentiate their treatment from all the other treatments out there,” says Jiang.

“We definitely need to standardize the way we are inspecting and checking the cells before it goes into a patient, but the flexibility allows each company to … show off their technology and allow for them to shine with the advancements that they've made,” Jiang adds.

Click above to view the full interview. BIO 2024 occurred on June 3–6 in San Diego, Calif.

Articles

Lonza’s Joe Garrity and Jerry Jiang discuss the latest trends and challenges in commercializing new CGTs. 

Trends and Obstacles in the CGT Field (BIO 2024)

Cell and gene therapies (CGTs) remain an important focus in the biopharma industry. During BIO 2024, Joe Garrity, senior director and head of Autologous Cell Therapy, and Jerry Jiang, clinical application specialist, Personalized Medicine, Cell and Gene Therapy, both at Lonza, discuss the latest trends and hurdles in the CGT space.

“Moving from the 2017 timeframe into 2020, we saw a heavy focus on a [significant amount of] money floating around focusing on autologous cell therapies and how we can better provide these life changing therapies to patients,” Garrity says. From the autologous cell therapy perspective, efficacy has been achieved, but the challenge remains that an autologous cell therapy is one manufacturing batch, or one dose, per patient. “The scaling is a little bit of a challenge,” Garrity says, noting, “This is where the allogeneic approach has taken over, and in the cell therapy space, we've really seen that shift … seen [focus] go from two-thirds autologous to one-third allogeneic to almost a 50/50 split.”

Garrity expects this trend to continue to where the industry may see a rise in allogeneic cell therapies, from a molecule number standpoint. “We're seeing a [bigger] influx of allogeneic cell therapies trying to provide a secondary option to commercially viable CAR-T [chimeric antigen receptor T cell]/CAR-NK [chimeric antigen receptor natural killer cell] drug products,” he states.

“At the end of the day it’s really about providing access and availability of cell therapies to those who really need it,” Jiang adds. “The cell therapy production process can be complex, and current solutions are not sufficient to be able to scale to the patient demand. So, as a result, new technologies are being developed to help reduce timelines and cost and improve scalability.”

Another issue Jiang points out is the difficulty in finding technicians who are able to work with and produce these therapies. “We've seen [many] different manufacturers try to figure out different ways of scaling down … either making the process faster or taking out other aspects of their manufacturing process to really streamline this process, as well as just reducing the costs [of these] therapies.”

Click the video above for the full interview. BIO 2024 occurred on June 3–6 in San Diego, Calif.

industry experts discuss the current outsourcing landscape in the post-COVID world 

Changes and Trends in the Outsourcing Landscape

The outsourcing landscape has seen many changes in recent years coming out of the COVID pandemic. Driven by a burgeoning pipeline of clinical-phase therapeutic candidates and the practical need for more advanced analytics, the contract services industry is hustling to meet the expected growth of new, more complex therapeutics to hit the market over the next decade. In this episode of 

 Video series, industry experts discuss the current outsourcing landscape in the post-COVID world and the changes the pandemic has enforced in the demand for outsourced bioprocessing services.

Eric S. Langer, president and managing partner, BioPlan Associates

Eric S. Langer has over 25 years experience in life sciences market assessment, valuation, marketing, management, and publishing. He been senior manager at biopharmaceutical supply companies and is an experienced biotechnology strategist. His team has advised hundreds of companies on marketing strategy development, valuation, pricing, and message strategy. Langer has also developed strategic plans based on quantitative analysis of market trends and buyer needs in valuation services, pricing, and analysis. He teaches graduate biotechnology marketing at Johns Hopkins University and biomedical valuation to the National Institutes of Health Graduate School

Jordi Robinson, chief commercial officer, Navin Molecular

Jordi Robinson has nearly 30 years of experience in the pharma and specialty chemicals industries, and is currently chief commercial officer at Navin Molecular, with responsibilities for all customer-facing activities, including business development and project management. Prior to joining Navin Molecular, he worked for six and a half years leading the European business development team for global contract development and manufacturing organization, Asymchem Laboratories, and has also held commercial and technical roles at Robinson Brothers and Endeavour Speciality Chemicals. He has a bachelor’s degree in chemistry from the University of Central Lancashire, UK.

Drug Digest is a tech talk video series with the 

® editors, who interview industry experts to discuss the emerging opportunities, obstacles, and advances in the pharmaceutical and biopharmaceutical industry for the research, development, formulation, analysis, upstream and downstream processing, manufacturing, supply chain, and packaging of drug products.

Biopharma Drug Development and Manufacturing

Videos

In this episode of Drug Digest, industry experts discuss the current outsourcing landscape in the post-COVID world and the changes the pandemic has enforced in the demand for outsourced bioprocessing services. 

Drug Digest: Changes and Trends in the Outsourcing Landscape

Lars Petersen, CEO, FUJIFILM Diosynth Biotechnologies discusses the company’s strategic goals and meeting market demand for mammalian cell culture capacity.

Demand Remains Strong for Mammalian Cell Culture Capacity (BIO 2024)

Demand for mammalian cell culture capacity remains strong and is growing, notes Lars Petersen, CEO of FUJIFILM Diosynth Biotechnologies, during BIO 2024. The company’s main strategic goals for this year centers around meeting this demand. “We are starting up a facility right now in Denmark (1), which is maybe the highest priority,” Petersen says, who also emphasizes that the company has “multiple CAPEX [capital expenditures] projects that we need to finish up.”

“In general, we are we shifting the business after COVID, after some of the financial challenges, to [focus on] what demand is most important … and we see a lot of new interest coming in. Being ready for that [demand] … is the most significant goal of the year,” Petersen says.

As for the company’s expansion of its Holly Springs, N.C., mammalian cell culture facility (2), Petersen explains that this expansion “has really been driven by demand … Demand is high.”

The market for mammalian cell culture needs more capacity, according to Petersen. “There's so much volatility shift and demand from new products coming in, shifting the market from innovators to CDMOs [contract development and manufacturing organizations] [for] new modalities [in treating diseases] like Alzheimer's. The pressure is on [for] other modalities that all end up with higher demand,” he says.

In terms of the future of therapeutic modalities, Petersen sees antibody drug conjugates making a comeback after about a decade and, conversely, a bit of slowdown in messenger RNA. “All these modalities, they really are difficult to foresee,” he observes. However, he expects that monoclonal antibodies will remain a major therapeutic modality for potentially the next 10–15 years, at least.

Click the video above for the full interview. BIO 2024 is being held in San Diego, Calif., on June 3–6.

1. FUJIFILM Diosynth Biotechnologies. FUJIFILM Diosynth Biotechnologies Breaks Ground For Major Expansion of Its Large Scale Biologics Production Facility in Denmark. Press Release, March 3, 2021.
2. FUJIFILM. FUJIFILM to Invest Additional $1.2 Billion to Expand its Large-Scale Cell Culture CDMO Business in North Carolina. Press Release, April 11, 2024.

Lars Petersen, CEO, FUJIFILM Diosynth Biotechnologies discusses the company’s strategic goals and meeting market demand for mammalian cell culture capacity. 

Developing a robust and reliable strategy for analytical studies of a biosimilar in development is crucial for a successful regulatory pathway. The importance of biosimilar products is tied to the push for more affordable, accessible biological treatments. However, bringing a biosimilar to market has strict challenges because the biosimilar developer must have a large set of analytical similarity data compared to the innovator biologic. In addition, the biosimilar developer must also contend with demonstrating interchangeability (1). 

Editor’s note: this article was published in the Pharmaceutical Technology Europe June 2024 issue.

Establishing biosimilar analytical studies

There are several key criteria to consider when establishing analytical studies for a biosimilar drug candidate to ensure its safety, efficacy, and similarity compared to the reference product, says Olaf Stamm, PhD, technical business development director, Biopharmaceutical Testing Solutions, Charles River Laboratories.

Among these criteria are comparability, biological activity, impurity assessment, and stability studies, Stamm notes. He explains that, for comparability, the biosimilar needs to demonstrate similarity to the reference product in terms of structure, function, purity, and potency. Analytical methods should thus be chosen or developed to compare critical quality attributes (CQAs) between the biosimilar and the reference product. “This involves assessing the physicochemical properties of the biosimilar, such as molecular weight, size, charge, and higher-order structure. Techniques [such as] mass spectrometry, chromatography, spectroscopy, and electrophoresis are commonly used for this purpose,” Stamm says.

The biological activity of the biosimilar should also be evaluated in analytical studies to ensure it matches the biological activity of the reference product. Analytical studies for determining biological activity may involve in-vitro assays, cell-based assays, or other relevant biological assays depending on the mechanism of action of the drug, Stamm remarks.

Identifying and quantifying impurities should include process-related impurities, degradation products, and contaminants. This is a crucial aspect of biosimilar development, Stamm notes. “Analytical methods should be sensitive enough to detect impurities at levels that are relevant to safety and efficacy,” he states. Stamm also points out that analytical methods should be established to identify and quantify residual host cell proteins to ensure they are within acceptable limits because their presence could impact safety and efficacy as well. “The evaluation of process-related impurities, such as residual solvents, reagents, and by-products, should be performed using appropriate analytical techniques,” he adds.

Meanwhile, stability studies are essential for assessing the biosimilar product’s shelf-life under various storage conditions. Analytical methods used for stability studies should monitor degradation pathways and stability-indicating parameters over time.

In biosimilars development, it is not enough to establish analytical evidence of the product’s biosimilarity to the reference product, but also its interchangeability. Luckily, establishing analytical studies for testing biosimilarity and interchangeability involves similar principles, Stamm explains. However, there are some key differences in the objectives and scope of these studies.

Stamm points out that the primary objective of analytical studies for demonstrating biosimilarity is to demonstrate that the proposed biosimilar is highly similar to the reference product in terms of quality, safety, and efficacy. “The goal is to show that any differences between the biosimilar and the reference product are not clinically meaningful,” he says.

In comparison, the objective of studies for interchangeability goes beyond demonstrating similarity. “[Interchangeability studies] aim to provide evidence that the biosimilar can be substituted for the reference product without any additional risk in terms of safety or diminished efficacy compared to using the reference product alone,” Stamm states.

Stamm further explains that interchangeability studies may involve additional clinical work. “Clinical studies for interchangeability are specifically designed to assess the impact of switching between the biosimilar and the reference product on safety and efficacy outcomes. These studies may include switching studies, pharmacokinetic (PK) and pharmacodynamic (PD) assessments, and immunogenicity evaluations in both naive and switch populations,” he says.

Both biosimilarity studies and interchangeability studies provide information that is crucial for regulatory authority evaluation. Stamm emphasizes that each type of study yields required data as explained in the following sections.

 According to Stamm, biosimilarity studies generate extensive analytical data comparing the biosimilar product’s CQAs with the CQAs of the reference biologic, including physicochemical characterization, biological activity assays, impurity profiling, and stability data.

 Meanwhile, clinical studies provide evidence of equivalent efficacy, safety, and immunogenicity between the biosimilar and the reference product in sensitive patient populations. These studies typically include PK/PD assessments as well as comparative clinical trials in relevant patient populations.

 Immunogenicity data—including an assessment of the development of anti-drug antibodies—is also a critical component of biosimilarity studies because these data help evaluate the potential risk of immunogenic reactions to the biosimilar.

 Interchangeability studies yield data on the safety and efficacy of switching between the biosimilar and the reference product, notes Stamm, who explains that these studies also include assessments of PK/PD, immunogenicity, and clinical outcomes following multiple switches between the two products.

Data from interchangeability studies also provide insights into patient outcomes from the impact of switching medications, including any potential risks associated with switching between the biosimilar and the reference product.

 Immunogenicity of the biosimilar product is also assessed in patients who undergo repeated switching between the biosimilar and the reference product.

 Regulatory authorities require evidence demonstrating that switching between a biosimilar and its reference product neither compromises clinical outcomes nor poses additional risks to patient safety or efficacy compared to using the reference product alone.

“Overall, both biosimilarity and interchangeability studies generate comprehensive data sets that regulatory authorities evaluate to assess the similarity, safety, efficacy, and interchangeability of biosimilar products compared to their reference products. These studies are essential for the regulatory approval of biosimilars and for ensuring their safe and effective use in clinical practice,” Stamm concludes.

1. Mirasol, F. Moving Biosimilars Forward in a Hesitant Market. 

ope®
Vol. 36, No. 6
June 2024
Pages: 32–33

When referring to this article, please cite it as Mirasol, F. Reviewing the Importance of Biosimilarity and Interchangeability. 

Biosimilar analytical assessments focus on demonstrating biosimilarity and interchangeability with the reference biologic.

Reviewing the Importance of Biosimilarity and Interchangeability

Founder and CEO of Atomic AI, Raphael Townshend, explores AI’s usefulness as a tool to characterize molecular structure and advance molecule engineering.

Applying AI to Molecular Structure (BIO 2024)

Raphael Townshend, founder and CEO of Atomic AI, a US-based emerging biotechnology company specializing in applying the fusion of artificial intelligence (AI) and structural biology for RNA-based drug discovery, discusses the use of AI as a tool for characterizing molecular structure and, in doing so, advance molecule engineering.

“At a high level, why we care about molecular structure is because the structures of molecules really determine what they do: structure determines function, so to speak. What we found in the last few years is that AI is a very powerful tool for understanding the structures of these molecules,” Townshend says. He notes that, traditionally, methods for understanding structure have names, such as X-ray crystallography, or nuclear magnetic resonance, or cryo-electron microscopy. “The issue is that they can oftentimes be very expensive to use and slow to use; it's a very bespoke process. Every single structure that is solved can be a very manual and involved undertaking. And what we've seen is that we can take all this work that's been performed in the field of structural biology, of understanding structures, and feed that into these AI algorithms that are now able to predict those structures in minutes or seconds instead. We've seen these orders of magnitude speed up our ability to model these structures and understand what they look like in their native environments,” he explains, emphasizing that AI enables a “rational drug design”.

“We're already starting to see that and bear fruit today. The use of [AI] … speed[s] up the process of … the whole drug discovery space, of doing the whole drug discovery process, so to speak,” he observes. He further explains that, as an additional layer on top of the traditional drug discovery process, AI can enable rapid screening, or a rapid search, through many possible drug candidates. “[T]he idea is that we're using these kinds of approaches to get to better, faster drugs, and getting things faster to the clinic and running those through a better rate.”

“As I like to say, AI is a cool thing of the day. It's a powerful tool, but it's a tool nonetheless,” Townshend adds. “It's not going to be a panacea; it's not going to solve every single problem under the sun. In particular, the areas where AI works well are those where there's [a significant amount of] data associated with it … and, so, in areas where that data [are] more limited … that can be an obstacle to the development of the correct AI applications in this space,” he notes when discussing some of the hurdles in implementing AI in the drug discovery space. Townshend says that, to address these limitations, the industry would need to collect additional datasets to push progress forward.

“Some areas to really think about, for example, are 

 studies where the amount of animal data that we might have might be relatively limited as compared to high throughput screening stages where you have [much] data, comparatively speaking. [T]hese are resolvable obstacles, but, today, the amount of data out there does not allow for the use of AI in its most advanced form across the entire drug discovery landscape. And that's not even speaking about the development cycle, [such as] clinical trials. There's even more complexity and even more limitations interpret the data. So, while there was this dream of one day using AI across the entire process, right now, there are some key areas where it's providing significant leverage, and we're working towards shoring up those additional gaps,” Townshend says.

View the video above for the full interview with Townshend. Townshend spoke at the 

New Tools, New Times: Chemical and Structural AI for Drug Discovery

 panel at BIO 2024 in San Diego, Calif., which is being held June 3–6.

Honeywell and the Future of Life Sciences Manufacturing

To learn more about manufacturing in the life sciences industry, 

sat down with Shawn Opatka, Vice President & General Manager of Life Sciences at Honeywell, at a recent INTERPHEX conference to discuss:

How automation technologies will likely evolve;

How Honeywell helps meet current industry challenges while maintaining an eye on the future;

What differentiates Honeywell from the competition in its approach to manufacturing and digitalization.

Shawn Opatka, Vice President & General Manager of Life Sciences at Honeywell, discusses how the company stands out in an industry that constantly evolves. 


Honeywell and the Future of Life Sciences Manufacturing 

Andrew Carnegie of Inaphaea BioLabs discusses the establishment of translational CROs and the role of PDCs in the drug discovery process.

A Look at Translational CROs and PDC Modeling (BIO 2024)

At this year’s BIO annual meeting, drug discovery and early phase analytics garner greater industry focus. Andrew Carnegie, PhD, head of Strategic Commercial Development, Inaphaea BioLabs, discussed some trends in the R&D analytical space and the advances being made to speed up the drug discovery process.

Carnegie explains that translational contract research organizations (CROs) aim to bring more clinically relevant humanized cell-based assays to the forefront early in the drug development pathway. Having clinically relevant data early on can help minimize the risk of failure of a compound/molecule in the preclinical and clinical stages of development, he notes.

“[A translational CRO] is really about providing design, input, and interpretation of results, in addition to just running the experiments, and sending a report based on the study,” Carnegie says. “We feel that better experimental design should lead to a more streamlined plan that is more efficient, and it provides our partners with better value for money. So, we're really looking at cutting down timelines and bringing more data points early on in the experiment so people can make decisions about their molecules early on, and hopefully be more successful in the preclinical and clinical stages.”

Carnegie also emphasizes that drug discovery is a challenging process with a low success rate of release of drugs. “Data suggests that poor prediction of efficacy remains the main cause of attrition and clinical failure. Around that, too, traditional drug discoveries relied on 2D cell cultures, often using non-human species, but animal disease models rarely reflect and represent the real causes, complexities, and phenotypes of human disease. This has really influenced a rise of 3D organoids and more clinically relevant, complex humanized cell models in paving the way for more accurate preclinical models that closely mirror human physiology and pathology,” he explains.

Thus, the humanization of the early phases of drug target validation has the potential to significantly improve how targets are validated for drug discovery, Carnegie adds. Among the tools now being used to humanize early phases of drug target validation are patient-derived cell (PDC) models. “The PDC is a primary cell culture, and it's established from the patient cancer cells, which were isolated directly from the tumor tissue or the patient body fluids. PDCs are maintained at a low-pass ID number, and result in a much higher clinical relevance than tumor cell lines. This really ties in with us wanting to bring humanized models earlier into the process to be more relevant and give more relevant clinical prediction and predictive data. The models are a great combination of accessibility and disease relevance,” he states.

Better early analytical work ultimately improves campaign success or the drug development process, Carnegie also emphasizes. “Our approach is to provide improved data by using more relevant 3D and hypoxia testing in disease-relevant systems, and bringing that [in] earlier … allows for more successful campaigns. [In addition], the kill-the-compound early approach is also very valid, allowing time and money to be better placed. So, with that early analytical R&D work, you can really get a [significant amount] of information upfront, [which] makes your decision easier on whether you'll take that molecule into preclinical and then into the clinic,” he remarks.

“PDCs are really the first step towards the true humanization of preclinical science and can be used to improve the translation of preclinical assets and enhance biological understanding,” Carnegie concludes.

Andrew Carnegie, head of Strategic Commercial Development at Inaphaea BioLabs, discusses the establishment of translational CROs and the role of PDC models in the drug discovery process.

The PharmTech Group sat down with Himanshu Gadgil, CEO of Enzene 

Continuous Manufacturing and Cost of Goods (BIO 2024)

Continuous manufacture of biopharmaceuticals is a hot topic in the industry. According to Himanshu Gadgil, CEO of Enzene Biosciences, continuous manufacturing has an impact on a company’s cost of goods. “For example, in a 1500-square-foot cleanroom, we can manufacture in a month currently around 10 kilograms of mAbs [monoclonal antibodies], and we are enhancing that platform where we should be able to manufacture on 40 kilograms of mAbs,” Gadgil says. Therefore, he explains, if a company wanted the same productivity at the moment, they would need a huge plant.

This is where continuous manufacturing is truly beneficial, Gadgil continues. “So, one of the biggest advantages of continuous manufacturing is cost of goods, because the operational cost is much lower than the conventional manufacturing, [because] the footprint is more compact, and at the same time, the productivity is also very high,” he says. “Because when you do perfusion, you get significantly higher cell densities almost five to 10 times higher cell densities than the conventional fed batch.”

When building a new continuous manufacturing facility, unit operations should be connected so that the process flows continuously, remarks Gadgil. “So, that whole process connecting is very, very challenging when you're starting out, but once you have the platform set up … the advantage of continuous manufacturing is that the footprint is very small, so you can easily scale out so once you have the platform, it is very easy to put more of the these and also from a geographical perspective,” he summarizes.

Click the video to watch the full interview. Enzene Biosciences will be showcasing its services at the BIO 2024 convention in San Diego, Cali from June 3–6.

The PharmTech Group sat down with Himanshu Gadgil, CEO of Enzene Biosciences to discuss the benefits and challenges of continuous manufacturing of biopharmaceuticals.

Lee Cronin, founder and CEO of Chemify, discusses the combination of digital chemistry, robotics, and AI in the drug discovery space at BIO 2024.

The Intersection of Chemistry, Robotics, and AI in Drug Discovery (BIO 2024)

As BIO 2024 moves into full swing, Lee Cronin, founder and CEO of Chemify, a UK-based company specializing in building up digital chemistry for chemical research, discovery, and manufacturing, discusses how the combination of digital chemistry, robotics, and artificial intelligence (AI) are advancing the drug discovery space.

According to Cronin, the concept behind digital chemistry is to connect chemical reactions to synthesize molecules in standardized hardware, or in a standardized way. This involves “using a programming language so that we can very faithfully reproduce chemistry, on demand and also to a given quality,” Cronin states. The process of computation in digital chemistry is akin to running code on a computer, he emphasizes. “The concept of digital chemistry … is pioneering this ability to turn code into molecules reliably at scale, on demand, and also for the creation of quite complex molecules, and even APIs,” he adds.

The combination of programming language, robotic architecture, and the use of data and AI is creating a new approach to not just making molecules but discovering and doing process optimization, practically in one tool chain, Cronin explains. “What this means is that we should be able to go from the discovery process to dreaming up new molecules to then the optimization and scaling,” he says.

It is not necessarily easy to dream up a molecule 

 and then translate that into producing that molecule on demand because some aspects may not be worked out, or the yields might be low, or there may be other blocks, Cronin points out. “What Chemify has done is we've built a series of approaches that allow us to digitize chemical reactions and have them ready on demand—a bit like building blocks,” he states. This approach allows the user to pull a code and go from a chemical reaction A to B or from a chemical reaction A to D, depending on preference. “[This approach] allows you to go from your target that you dream of, to then work out what particular reactions you must do ahead of time, and, more importantly, allows you to restrict your search of chemical space when you're [early in the research process], when you're dreaming up new molecules to reactions you know how to do, [and] so this increases the speed that you can discover new molecules and make new molecules, and go through the cycle of design–make–test–analyze,” Cronin explains.

Of particular significance is that once a new molecule has been made, once the code has been established, that code can be reused and optimized to scale further down the line, Cronin points out. “You've got this programming language and these reactions and the robots that run it; [therefore], you're able to update your process continuously with the weight of the insights that you get,” he adds. With these chemical reaction insights, the data and methods can then be processed through AI, allowing for optimized yields, Cronin states.

View the video above for the full interview with Cronin. Cronin is speaking at the 

Lee Cronin, founder and CEO of Chemify, discusses the combination of digital chemistry, robotics, and AI in the drug discovery space.

Featured Content

Digital Transformation in Pharma Manufacturing

Behind the Headlines, Episode 23

ICH Q12 and Post-Approval Changes

Drug Digest July 2025

Bio/Pharma's Tariff Response