OR WAIT null SECS
This compilation allows readers to adjust their thinking to appreciate the full impact certain select technologies will make on the industry by 2026.
Devoting time to track what developments will impact bio/pharmaceutical manufacturing isn’t easy, unless (like an editor of this publication) it’s your primary task. In a framework of descending order of impact, the first trend discussed in this article is messenger (mRNA) applications beyond vaccines. At the end of this list is bringing pharmaceutical manufacture right to the patient’s bedside. For near-patient and distributed manufacturing, FDA calls for not only fresh approaches but the willingness to use new ways of thinking to achieve this goal. Being focused on the year 2026, we allow the reader time and space to better reset, and prepare for only the most seismic events.
“The very essence of what makes mRNA a great way of delivering vaccines is the very real challenge of making them anything other than fit for that purpose, namely their inherent ability to cause activation and alarm within our highly sophisticated adaptive immune systems,” says Stephen Rapecki, director, Experimental Therapeutics, UCB. “We need to devise improved means to disguise and deliver both mRNA itself and also it’s delivery packaging, if that can be accomplished,” continues Rapecki. “The second challenge is delivering mRNA to its chosen cell or organ. mRNA vaccines administered subcutaneously most likely deliver their immunogenic payload to antigen presenting cells at the site of injection and to draining lymph nodes. This allows small and targeted doses of vaccine to be amplified as the immune reaction is the intended outcome not the production of the protein per se. To deliver a protein to correct a condition or replace a defective version of a protein will require much larger amounts than for immunization, perhaps by factors of up to a thousand. Such manufacturing challenges though are not insurmountable given the exciting opportunities mRNA offers drug hunters,” he contends.
The next hurdle, common to any drug therapy, is liver metabolism and toxicity. An approach here, Rapecki continues, “is to attach a targeting portion to your LNP [lipid nanoparticle], which typically could be a peptide, antibody, or antibody fragment. This doesn’t avoid the liver but can potentially swing the selectivity in favor of your cell type of interest. The final challenge to expanding mRNA beyond vaccines could be a strength or weakness depending on your point of view. This is the transient nature of mRNA expression which can vary from hours to many days but not the months or years that might unlock applications which currently are the domain of viral delivery. The iterative development of non-natural mRNA sequences, self-amplifying mRNA and now circular mRNA are beginning to extend the length of protein expression delivered by mRNA, but it is still envisaged that mRNA therapies outside the vaccine field will need repeat dosing to be truly effective. This leads to which applications will come after infectious disease vaccines. The low hanging fruit will be not to avoid an immune response, but to rely on it and deliver cancer vaccines, many of which could be personalized through sequencing tumour antigens to discover which give the best anti-tumor responses ... Beyond vaccines lies the non-immunogenic applications already mentioned. Assuming, and it’s a very big if, immunogenicity is greatly reduced, the next application is likely protein delivery to enclosed organs such as the eye, brain, etc. These will need larger doses and repeat administration so the durability of these responses will be key. In the periphery non-immunogenic targeted LNPs, which have the most scientific hurdles to cross, also have the potential to open the largest therapeutic space. Here you can envisage altering your own T cells to temporarily become CAR-T [chimeric antigen receptor T cell] cells circumventing the need for expensive cell therapy and with a safety profile that could work outside of oncology. Delivering a protein to cells in the blood altering their sensitivity in the case of autoimmunity should also be a possibility giving dosing regimens similar to current biologic drugs.”
Donald Ingber, founding director, Wyss Institute for Biologically Inspired Engineering at Harvard University, believes Organ Chip technology is at the tipping point when it comes to drug discovery and personalized medicine. He points to a study where scientists performed a comparison between animal models and human Liver Chips that shows these chips offer a way to predict drug-induced liver toxicities (1).
“Perhaps even more important for their acceptance by regulatory agencies and the pharma world, this study included an economic analysis that estimated drug developers would save about $3 billion per year if this one animal model were replaced by Organ Chip technology, given the huge costs of drugs failing once they get into clinical trials,” says Ingber. “My hope is that this will catch the eye of those in C-suites, which would ensure this transition towards a faster and less expensive way of developing safer and more effective drugs. At the same time, the ability to create Organ Chips lined by patient-derived cells, which we do standardly, opens the possibility of an approach to personalized therapeutics in which not only are better drug choices made, but the administration regimens—how frequently the drug is administered, by what route, and at what dose—may be optimized as well.”
Tissue Dynamic, an emerging organoid company, estimates (in a dramatic claim) that the company could cut drug development costs by 40–80%, and time required by 30–50% overall. Their approach is to ab initio embed sensors into the organoid while its being grown, which allows AI-driven computation to directly interrogate biology every step along the development process. “This allows the robot to start screening drugs against different models of disease. It can perform, by itself, safety assessments in the microtissues and identify the drug that works best and causes the least damage to human organs, and it does this extremely fast. We can do it in 19,000 tissue samples at once. It is the equivalent of [testing on] 5000 patients,” said Yaakov Nahmias, founder and chief scientific officer of Tissue Dynamics LTS (2).
In a presentation at the 2022 PDA-FDA Joint Regulatory conference, Martin Van Trieste spoke about quality 4:0, six sigma, and the date deluge, saying, “We’re now using machine learning and AI, and that will really help eliminate failures, eliminate deviations, eliminate non conformances, and get past what I call blind compliance.”
At the conference, Van Trieste spoke about saving an in-process batch of protein product at Amgen as a case example, before proclaiming that because of AI, “the future looks really bright for patients with improved safety, reliability, and quality, and all at a lower cost, some of which will be passed on to the consumer. Now if the future is bright for this group of people, it must be bleak for somebody else. And it’s going to be bleak for the dinosaurs of the industry, for the large quality organization that have been built around testing and inspecting the product, because if you are doing AI, you don’t need large testing organizations. The computer will not allow a mistake to happen, and it will safety check everything at the end … It’s really good for the patients. It’s not good for the quality unit, so I suggest that you really learn data analytics, you really learn AI‚ become that resource in the company, because that’s how you’re going to keep your job in the future.”
In concrete terms, Nicholas A. Geisse, CSO of Curi Bio, explains, “Where we’ve been using AI at Curi is to unbias the observer. We routinely use AI/ML routines to analyze our imaging data in an unbiased way and use it to find the unquantifiable subtle idiosyncrasies that are within the data. One thing that always frustrated me was that for certain procedures, for example stem cell differentiation, we’d have to grab one specific expert to look down the microscope and give a thumbs up or a thumbs down for our go/no go criteria.” That was the past.
According to a press release, PictorLabs (3) uses deep learning algorithms to stain tissues in silico, producing near-instantaneous virtual stains, claiming, “From a single unstained tissue sample, PictorLabs’ proprietary platform can produce an unlimited number of virtual stains that are indistinguishable from analogous chemical stains.” To even imagine this requires a robust adjustment of our preconceptions.
Drug recalls, warning letters, and persistent repeated drug shortages have been a drag on both the bottom line and the perception of the pharmaceutical industry for many years. FDA has now moved ahead in its plans to push for higher corporate quality culture through its QMM assessment program. In an article published in Pharmaceutical Technology (4), the authors state their experiences running the overseas pilot program. The program assessed eight overseas excipient companies’ quality culture and business process performances. “While FDA provides oversight of the site quality management processes and product quality via CGMP [current good manufacturing practice] inspections, and other surveillance methods, there are currently no comparable regulatory tools that examine a site’s business processes and how well they are integrated with quality objectives. QMM fills that much needed gap.”
In an interview with PharmTech, Somnath Mishra of Shabas Solutions pointed to senior management’s role in controlling aspects of quality (5). “They’re the ones that control the purse strings and the decisions that are made that actually breathe life into a quality system ... Those people can better solve some of the pernicious intractable problems that exist … Pharmaceuticals are simply recognizing the initiatives and successes that these other industries have achieved, and realizing these only so much that can be done at the technical level, …. you can train technicians, provide SOPs [standard operating procedures], specifications … You can oversee with managers, supervisors, even director level personnel, and still there are problems. So, it was these other industries that solved that. They illuminated the source of some of the pernicious problems, and it pointed back to senior management … [who] had underappreciated the quality aspects of corporate culture.”
To clarify the reasoning to include QMM in this list of trends, QMM won’t promote pharmaceuticals to make a bigger impact on patients directly, but it will make a very big impact on how the industry conducts itself internally, in particular, at C suite levels, and how better outcomes and efficiencies cascade outwards.
One of the constraints to cell and gene technology (CGT) growth is to scale vector production. “By its very nature, transient transfection is an inconsistent process and really limits the ability of the field to make significant yield improvements,” says Clive Glover, general manager, gene therapy, Pall Corporation. Comparatively monoclonal antibodies (mAbs), “are three to five orders of magnitude greater than when the field started out. We are aiming to reproduce this in the viral vector field, but it turns out to be significantly more difficult to make a stable producer cell line for viral vectors due to the inherent toxicity of some of the proteins to the producing cell,” Glover observes.
Optimally, we might have producer cell lines that can produce vectors without the need of transient transfection, but creating high-titer stable producer cell lines is difficult. “In time, researchers rediscovered the potential for gammaretrovirus in CGT, focusing where oncogene promoter-adjacent insertion is less of a concern, including CAR-T therapies—and this is where the industry stands now, at an exciting nexus point where potential is becoming reality,” Bill Vincent, founder and executive chairman, Genezen remarked (6).
Glover elaborates on his earlier point saying, “CEVEC, a Germany company, recently acquired by Cytiva, has figured out how to solve this problem by putting the genes required for viral vector production behind an inducible switch that can be turned on once the producer cells have been grown up to their final production volume.”
Adam Fisher, director, Science Staff, Office of Pharmaceutical Quality, Center of Drug Evaluation and Research (CDER), FDA, rhetorically asked (7), “If a future with distributed and point-of-care manufacturing doesn’t look like traditional brick-and-mortar manufacturing, what might it look like? Prefabricated, mobile, modular manufacturing units might move frequently between different geographical locations. Manufacturing units at multiple locations, perhaps even 3D [three-dimensional] printers at patients’ bedsides may operate under a single remote quality management system. This is no longer science fiction. FDA has seen some of these technologies from developers of distributed manufacturing processes.” While FDA’s CDER does not have any approved drugs in its current purview made with distributed or point-of-care technology, experts know they are coming.
CDER’s outreach is asking input by Dec 13, 2022 to: “How can manufacturers ensure location changes do not impact product quality?” The article ends by quoting FDA’s Larry Lee, “I think pharmaceutical manufacturing is on the verge of reconstruction; we have reached the point where change is necessary to improve quality and access” (7). A sentiment echoed by the Journal of Cancer Gene Therapy (8), “…cryopreservation has become a critical area of interest in cell-therapy manufacturing, as issues of cell viability, functionality, and patient safety become increasingly important to resolve as more therapies reach the market. For autologous cell-based applications, many have argued that the best place for cell production is the ‘bedside’.”
1. Ewart. L.; Apostolou, A. et al. Performance Assessment and Economic Analysis of a Human Liver-Chip for Predictive Toxicology. Commun Med Nature 2022.
2. Nahmias Y. Biologic Drug Development and Manufacturing. Drug Solutions Podcast, PharmTech.com. April 2022.
3. PictoriLabs. PictorLabs Launches with More Than $18.8 Million to Advance Transformative Virtual Staining. Press Release. Dec 1. 2022.
4. Mishra, S.; Hauck, W.; Royal Z.; and Michalik R., Introduction to Pharmaceutical QMM Model: QMM Assessment to Promote Pharmaceutical Operational Excellence, Pharm Techn. 2022 46 (12).
5. FDA Quality Management Maturity (QMM) Overseas Pilot Progran Findings: Going Beyond the Regulations, Drug Solutions Podcast, PharmTech.com. Dec 7, 2022.
6. Mirasol F. Driving Manufacturing Improvements Through Viral Vector Advances. BioPharm Intern 35 2022 (8) 18–21.
7. Fisher, A. Nurturing Manufacturing Agility, Pharm Technol. 2022 46 (12) 28-6. 29.
8. Kaiser A.; Assenmacher, M. Towards a Commercial Process for the Manufacture of Genetically Modified T Cells for Therapy. Cancer Gene Therapy. 2015.
Chris Spivey is editorial director for Pharmaceutical Technology.
Vol. 47, No. 1
When referring to this article, please cite it as C. Spivey. Six Approaches Making the Most Significant Impact in the Future. Pharmaceutical Technology 2023 47 (1).