Feliza Mirasol is the science editor for 

Feliza Mirasol

On Feb. 5, 2024, Novartis announced that it intends to acquire MorphoSys, a Germany-based biopharmaceutical company focused on oncology therapeutics, for €68 per share, or €2.7 billion (US$2.9 billion) in aggregate, in an all-cash transaction. The acquisition, which was unanimously approved by the boards of both Novartis and MorphoSys, is expected to close in the first half of 2024, subject to customary closing conditions. Until closing, MorphoSys will continue to operate as a separate, independent company.

With the acquisition, Novartis gains pelabresib (CPI-0610), a late-stage investigational small-molecule bromodomain and extra-terminal domain (BET) inhibitor for treating myelofibrosis (MF). Pelabresib is being evaluated in combination with ruxolitinib as a potential first-line treatment for MF. The combination recently met its primary endpoint of spleen volume reduction in a Phase III clinical trial (MANIFEST-2) in Janus kinase inhibitor-naive MF patients. A regulatory filing is planned with FDA for the second half of 2024.

Novartis also gains tulmimetostat (CPI-0209), an early-stage investigational dual inhibitor of enhancer of zeste homolog 1 and 2 (EZH1 and EZH2) proteins currently being tested in patients with solid tumors or lymphomas.

“We are excited about the opportunity of bringing pelabresib, a potential next-generation treatment combined with ruxolitinib, to people living with myelofibrosis, a rare and debilitating form of blood cancer,” said Shreeram Aradhye, president, Development, and chief medical officer, Novartis, in a company press release. “With the planned acquisition of MorphoSys, we aim to further strengthen our … pipeline and portfolio in oncology, adding to our capabilities and expertise. Building on our long-standing development partnership with MorphoSys, we look forward to continuing our work together to realize the full impact and value of their investigational medicines for patients with unmet needs.”

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Through a €2.7 billion (US$2.9 billion) acquisition of MorphoSys, Novartis will get pelabresib, a late-stage drug candidate in development for cancer treatment.

Novartis to Acquire MorphoSys for Roughly $2.9 Billion

On Feb. 6, 2024, Purolite, an Ecolab company and a manufacturer of synthetic and agarose-based bioprocessing resins, and Repligen announced that they have commercially launched Praesto CH1, a new 70 μm (micron) agarose-based affinity resin designed. The resin is designed to purify specialized monoclonal antibodies (mAbs) such as bispecifics and recombinant antibody fragments.

This latest innovation was developed for commercialization by Purolite under a multi-year strategic partnership with Repligen. The innovation combines Purolite’s manufacturing process for its patented Jetted beads with Repligen’s ligand technology. The goal is to address previously unmet challenges in specialized mAb purification.

The new CH1 purification resin strengthens Purolite’s current protein A resin portfolio as it has been shown to demonstrate high selectivity for antibodies and related fragments containing the human first-constant domain of the heavy chain, or the CH1 domain. According to a company press release, this characteristic allows for the capture of bispecific antibodies and antibody fragments, as well as the removal of mis-paired species. The new CH1 resin thus offers an effective alternative for the purification of antibody variants when protein A resins are not suitable, according to the release.

“The launch of Praesto CH1 represents the latest offering in Purolite’s growing innovation toolbox for the purification of biologics. Our strategic partnership with Repligen brings leading technologies together to unlock new purification strategies that address our customers’ increasingly diverse biotherapeutic molecules, and the unique purification challenges that these can present,” said Jennifer Sorrells, vice-president of Research and Development, Purolite, in the release.

“It’s fantastic to see the Praesto CH1 resin come to market through our partnership with the Purolite team … This cross-linked agarose-based resin was specifically and successfully engineered for high dynamic binding capacity to the CH1 region of antigen-binding fragments from human immunoglobins (IgGs) and monoclonal antibodies (mAbs), and we believe it is particularly well positioned for market success,” said Ralf Kuriyel, senior vice-president of Research and Development, Repligen in the release.

Purolite and Repligen have commercially launched a new CH1 affinity resin for the purification of specialized mAbs.

Purolite and Repligen Launch New Affinity Resin

On Feb. 5, 2024, Quantum-Si, a US-based protein sequencing company, announced the launch of new platform enhancements for its Platinum protein sequencing platform. The new enhancements, Protein Sequencing Kit V2, allow for:

increased sequencing performance with assay improvements, which include the addition of a new amino acid recognizer

the ability to identify unknown proteins with advanced analytical and inference tools

approximately a three-fold reduction in cost per amino acid.

In tandem with the launch, the company’s CEO and executive team released a video outlining the recent enhancements, highlighting the significance of the newly launched kits. The team also outlines the company’s strategic initiatives for 2024. The video can be viewed on the company’s website.

“Our newly introduced capabilities will provide researchers with additional insights into the proteome that have the potential to unlock scientific discovery only possible at the level of single amino acid recognition,” said Jeff Hawkins, CEO, Quantum-Si, in a company press release. “With Platinum, we are striving to make protein sequencing accessible to every lab everywhere, and, now, with our V2 Sequencing Kits, more insights are possible with greater cost efficiency so that even more scientists can easily incorporate Platinum into their workflow.”

“These advancements not only ensure increased robustness and performance but also introduce novel protein inference analysis software, empowering customers to discover unknown proteins in their samples,” said Grace Johnston, chief commercial officer, Quantum-Si, in the press release. “With this launch, Quantum-Si is set to deliver unparalleled insights into protein characterization and function, catering to the evolving needs of our diverse customer base. Further, it reflects the value of next-generation protein sequencing as we expect that our platform will open new doors to unprecedented biologic insights and the molecules of life.”

The addition of another amino acid recognizer as well as improvements in surface chemistry, reagents, and software expand the proteome coverage of Quantum-Si’s Platinum sequencing platform.

Quantum-Si Launches Platform Enhancements for Protein Sequencer

On Feb. 5, 2024, Novo Holdings, a wholly owned company of Novo Nordisk Foundation and the parent company of Novo Nordisk, announced that it has entered into a merger agreement with Catalent under which Novo Holdings will acquire Catalent in an all-cash transaction. The transaction values Catalent at $16.5 billion.

Under the agreement, Novo Holdings will acquire all outstanding shares of Catalent at a price of $63.50 per share in cash, a premium of 16.5% to the closing price of Catalent’s common stock as of Feb. 2, 2024. The merger is expected to close by end of 2024, pending customary closing conditions. Following the close, shares of Catalent will no longer trade on the New York Stock Exchange, and Catalent will become a private company.

Novo Holdings intends to sell three of Catalent’s fill/finish sites and related assets acquired in the merger to Novo Nordisk shortly after the merger closes. The three sites are in Anagni, Italy; Bloomington, Ind., in the United States; and Brussels, Belgium.

“Over the past several years, Catalent has built a comprehensive end-to-end offering of services and capabilities to drive innovation in the healthcare system and improve patient outcomes. This transaction is a testament to our team’s hard work and dedication to this mission, and I am incredibly excited for this next step in our journey. We look forward to benefiting from Novo Holdings’ significant resources to accelerate investment in our business and enhance key offerings as we continue to offer premium development and manufacturing solutions for pharma and biotech customers,” said Alessandro Maselli, president and CEO, Catalent, in a company press release.

“We are excited to partner with Catalent as it enters a new phase of growth and accelerates its mission to develop, manufacture, and supply products that help people live better and healthier lives. With our expertise and track record of investing in high quality life sciences businesses, we believe Catalent is a very good strategic fit … Importantly, our acquisition of Catalent is aligned with our mandate to invest in high quality life sciences companies for the benefit of the Novo Nordisk Foundation’s mission and philanthropic causes,” said Kasim Kutay, CEO, Novo Holdings, in the press release.

Novo Holdings has entered into a merger agreement with Catalent and will acquire Catalent in a deal valued at $16.5 billion.

Novo Holdings to Acquire Catalent in Deal Valued at $16.5 billion

The current trend in biopharmaceutical development is to place more thorough emphasis on molecule characterization early in the drug development process. Thus, pharmacokinetic (PK) and pharmacodynamic (PD) studies developed during preclinical development are crucial.

Being able to characterize the relationship between PK (i.e., how the body interacts with a therapeutic/drug over the duration of exposure to that substance) and pharmacodynamics (i.e., dose effects) is considered an important tool in the drug discovery and development process. Implementing PK/PD studies in the early phases of drug discovery projects facilitates a successful transition from the discovery phase to the development phase (1).

Importantly, establishing an effective PK/PD study design, analysis, and interpretation allows scientists to:

illuminate the relationship between PK and PD

elevate the understanding of a drug’s mechanism of action (MOA)

identify PK properties for further improvement and optimal compound design (1).

Meanwhile, using a PK/PD modeling approach can increase translation of a compound’s 

 animal studies and improves the transition of study results from the preclinical setting to the clinical setting. In fact, it is the effective translation of preclinical data that is critical for developing the design of appropriate and successful clinical trials (1).

Having a sound understanding of a lead compound’s PK/PD relationship provides a PK basis for what to expect in the therapeutic index of that compound. Having this understanding also aids in the design of proper dose regimens for proof-of-concept studies in the clinical development phases. Important factors to consider for maximizing the use of a rigorous PK/PD analysis include establishing a dataset that adequately captures the following profiles: concentration vs. time and effect vs. time. Furthermore, the following should be incorporated in the PK/PD model:

a fundamental understanding of the biological pathway being agitated

a consideration of unbound concentrations

sound statistical and mathematical output.

The bioanalysis of large-molecule therapeutics (e.g., peptides, proteins, monoclonal antibodies, antibody drug conjugates) is typically conducted in a biological matrix, typically serum or plasma (2). Bioanalysis of large molecules is often performed using ligand binding assays such as enzyme-linked immunosorbent assay (ELISA) or electrochemiluminescence (ECL), or, in some cases, hybrid liquid chromatography-tandem mass spectrometry methods (3). It is important to keep in mind that PK profiles of large-molecule therapeutics differ significantly from small molecules based on the absorption, distribution, metabolism, and excretion of large molecules compared to small molecules. Such differences will affect the PK profile of a large-molecule therapeutic (3).

Modeling approach. Dosing requirements for new large-molecule therapeutics should be assessed early; this early assessment must, therefore, be an integral component of the developability strategy of a drug discovery program. For instance, with early dosing requirement assessments, a developer can evaluate whether an extremely high dose is needed to achieve the targeted pharmacological effect. If so, the developer may consider that it is not feasible to advance a potential candidate to clinical or even commercial stages of development without also developing a high-concentration formulation or else maximizing yield in the manufacturing process (4). The use of mechanistic PK/PD models, therefore, come into play, which use knowledge and available competitor data at the early stage of drug development—including the biophysics of the intended target(s) as well as the physiology of the disease—to rationally inform the drug design criteria (4).

., “[m]echanistic PK/PD modeling links PK to PD through a biophysical description of the therapeutic MOA and relevant target biology” (4). The paper goes on to describe that, with a mathematical description of these key MOAs, mechanistic PK/PD models can then be used to support decisions across the drug discovery and development pipeline.

Mechanistic PK/PD modeling can also be applied to decisions in later stages of drug development. To support later-stage drug development and clinical-stage decisions, mechanistic PK/PD models are dependent on the integration of data from 

 preclinical studies as well as data from clinical PK studies, biomarker evaluation, and response studies. “This approach has improved extrapolation capabilities to predict drug efficacy and safety in humans compared to empirical PK/PD modeling; therefore, it is also commonly used in translational research,” according to Grant 

Thus, mechanistic PK/PD modeling has been shown to successfully guide early drug discovery decisions. This approach allows researchers to define a range of drug properties that are expected to achieve the most robust response with respect to receptor occupancy and/or target engagement. Moreover, mathematical modeling can enable early no-go decisions and facilitates the integration of development considerations into the decision-making process early on that then reduces risk in later stages of the development process. Importantly, mechanistic PK/PD models can be applied to recombinant proteins and peptides, in addition to antibody therapeutics, which is an important factor when working with novel biotherapeutic modalities or with biomolecules that are not yet well understood (4).

Early considerations in the drug development process also include how the potential or selected candidate will be delivered 

 to achieve the desired therapeutic effect. As such, PK/PD studies can also be applied to large molecule drug delivery, and strategizing a formulation and drug delivery method needs to be factored in during the early development phase. The advancement of technologies in the biopharma industry has led to the development of increasingly complex biomolecules and more sophisticated drug delivery systems. This has also led to increasingly complex drug absorption and disposition processes following administration with these drug delivery systems (5).

Because PK/PD modeling allows for the separation of drug, carrier, and pharmacological system-specific parameters, it has been used to improve the understanding of the 

 behavior of these complex delivery systems. Thus, PK/PD modeling helps in the development such drug delivery systems.

However, while PK/PD modeling has been helpful in advancing drug development, it poses several challenges. For instance, assumptions used to simplify the drug delivery process so as to plug into the PK/PD model may not be appropriate for the molecule of the delivery system at hand. To start with, any assumptions used must be reliable, and this requires a detailed understanding of the physiological system and drug delivery system at play. Lacking the relevant information makes it difficult to validate the assumptions at the start (5).

Modeling assumptions are typically based on prior knowledge and experience, and thus having assumptions helps to fill missing pieces in existing information as well as simplifies the understanding of a complex system. Modelers should take heed and acknowledge, however, the limitations of the model. Moreover, development of PK/PD models should be fit-for-purpose.

Extrapolation from animal studies to human studies based on PK/PD modeling is another challenge, particularly when it comes to scaling. Some approaches that have been considered to minimize errors with scaling include (5):

Selecting the appropriate animal species for scaling to humans

Employing allometric scaling using multiple species (to both minimize the error and increase the accuracy of prediction)

Where, for some pharmacological systems, the scaling method from animal to human has already been established, use available prior information.

1. Tuntland, T.; Ethell, B.; Kosaka T.; et al. Implementation of Pharmacokinetic and Pharmacodynamic Strategies in Early Research Phases of Drug Discovery and Development at Novartis Institute of Biomedical Research. 

, 174. DOI: 10.3389/fphar.2014.00174
2. Pacific BioLabs. Large Molecule Bioanalysis. 

pacificbiolabs.com/large-molecule-bioanalysis

 (accessed Jan. 15, 2024).
3. Medpace. PK Studies. 

medpace.com/labs/bioanalytical-lab/pk-studies

 (accessed Jan. 15, 2024).
4. Grant, J.; Hua, F.; Apgar, J. F.; Burke, J. M.; Marcantonio, D. H. Mechanistic PK/PD Modeling to Address Early-Stage Biotherapeutic Dosing Feasibility Questions. 

 (1), 2192251. DOI: 10.1080/19420862.2023.2192251
5. Zou, H.; Banerjee, P.; Leung, S. S. Y.; Yan, X. Application of Pharmacokinetic-Pharmacodynamic Modeling in Drug Delivery: Development and Challenges. 


Volume 48, No. 2
February 2024
Pages 32–33

When referring to this article, please cite it as Mirasol, F.Addressing PK/PD Study Design Early in Development.

Strategizing a PK/PD study approach in early phase development facilitates a successful clinical progression.

Addressing PK/PD Study Design Early in Development

Lonza announced on Jan. 30, 2024 that it has formed a collaboration with Oxford Nanopore Technologies, a provider of nanopore-based molecular sensing technology, to validate—according to current good manufacturing practices (CGMPs)—and commercialize a novel test that accurately determines multiple critical quality attributes (CQAs) of messenger RNA (mRNA) products. According to a company press release, this test is the first-of-its-kind; it directly sequences both the DNA template and the mRNA.

The collaboration aims to address industry and regulatory need for a CGMP-grade common testing method that can simplify and streamline mRNA manufacturing. Under the agreement, Lonza and Oxford Nanopore will focus on adapting the latter’s technology to make it applicable to mRNA production analysis and quality control (QC). The nanopore-based sequencing method makes it possible to use one technology platform to simultaneously measure several quality attributes in mRNA products within the same manufacturing site. Once commercialized, the test aims to substantially shorten analytical testing time and thus reduce the manufacturing timeline for mRNA products.

Through the collaboration, Oxford Nanopore will tech transfer its in-house-developed workflows to Lonza for GMP validation. Oxford Nanopore’s GridION device will be used to generate real-time data and reporting. After validation has been achieved, Lonza intends to include the sequencing technology in its analytical development workflow offering. The company will also support Oxford Nanopore’s efforts to achieve stringent quality requirements for QC compliance. Lonza will pre-validate several CQAs of mRNA products for the novel test at its Geleen, The Netherlands-based analytical development laboratory. Tech transfer will happen at Lonza’s QC laboratories on the same site for CGMP-compliant method validation.

“While the mRNA market is fast-expanding, as a relatively new modality, it still relies on the use of traditional analytical technologies. Faster and more effective mRNA analytics could simplify the regulatory review process and accelerate the development path. This collaboration underlines the commitment of Lonza and Oxford Nanopore to bring innovation to the market. Our shared objective is to simplify testing processes to bring mRNA therapies to market quicker,” said Torsten Schmidt, head of mRNA Business Unit, Lonza, in the press release.

“mRNA technologies have already delivered a profound impact in recent years, and the industry is growing into many novel areas, including personalized cancer vaccines. With Lonza, we are excited to develop an enabling technology by developing the first GMP-grade test to analyze multiple critical quality attributes of mRNA products. Nanopore sequencing offers a transformational new approach with its one-of-a-kind ability to sequence native RNA to deliver robust and accurate testing of multiple critical quality attributes, 

 and with rapid turnaround times. Not only may this help with pandemic preparedness, but it could also be crucial in ongoing R&D advancements for mRNA therapeutics,” said Gordon Sanghera, CEO, Oxford Nanopore Technologies, in the release.

Under a new collaboration, Lonza and Oxford Nanopore aim to commercialize a CGMP-validated test for advanced analysis of mRNA products.