08 | Apr | 2024

Chinese

Nonhuman primates (NHPs) are highly translational models in drug development and are widely used in preclinical efficacy and safety studies¹. Due to genotype similarities with humans, in vitro NHP stem cell lines have started gaining traction within the drug discovery community as translational models to evaluate preclinical efficacy and safety. Initially, pluripotent stem cells were initially developed from mice followed by humans. Human embryonic stem cells (ESCs) were first described in 1998² but faced significant challenges due to ethical issues and societal pressures. A major breakthrough was reported in 2006 when Yamanaka and colleagues described the development of human induced pluripotent stem cells (iPSCs) that were reprogrammed using specific transcription factors³. Since the first report, human iPSC lines have been widely developed and used for basic research, in vitro assays for drug development and are the foundation of cell therapies and regenerative medicines. Methods and protocols to develop novel human stem cell lines are widely available but, interestingly, the development and use of NHP stem cell lines have somewhat lagged behind. One reason could be that reprogramming NHP cells to iPSCs has lower efficiency and the protocols are more complex compared to human cell reprogramming¹. For example, NHP iPSC reprogramming require feeder cells and xenogeneic serum and depending on the NHP species, can take several weeks¹. Despite technical challenges, NHP stem cell lines have been successfully developed and are being used in multiple applications including regenerative drug development and cell therapies as well as primate developmental biology studies.

One of the key applications of NHP pluripotent stem cells is preclinical testing of cell therapies. During preclinical development, the dosage, route of administration, implantation efficiency, short- and long-term efficacy and host rejection need to be evaluated. NHP iPSCs are well suited to test cell therapies in NHP models prior to clinical trials4. NHP models are well suited for longitudinal studies to evaluate host rejection and graft vs host disease as they have an extended life span and large bodies that is amenable to imaging, surgical and sampling methods that are used in the clinic⁴. NHP pluripotent stem cells have been reported to be similar to human stem cells so the preclinical data on cell therapies is translatable to human patients. A key application of NHP pluripotent stem cells is the evaluation of immunogenicity responses to cell therapies. The easiest approach to avoid immune reactions is to focus on autologous cell therapies, which have limited scalability and require complex supply chain logistics among other challenges. Allogeneic cell therapies are scalable and easier to manufacture but typically induce host rejection both locally and systemically. Therefore, in order to safely develop allogeneic cell therapies, it is necessary to analyze immune risk and tissue damage caused by the host immune system. The NHP immune system is very similar to human so testing NHP pluripotent stem cell derived therapies in an NHP model is a good model to evaluate immunogenicity⁴.

NHP pluripotent stem cells have applications in regenerative medicine. For example, researchers in Göttingen Germany reported a new method to reprogram NHP skin fibroblasts to iPS cells that were successfully differentiated into cardiac muscle cells¹. The NHP iPSC derived cardiomyocytes had self-organizing capacity and were shown to generate beats via microelectrode array (MEA) analysis¹. Another growing area of interest is regenerative therapies for neurodegenerative diseases such as Parkinson’s disease (loss of dopaminergic neurons) and Huntington’s disease (loss of basal ganglia neurons). Over the past decade, a few groups have developed autologous transplantation NHP models for Parkinson’s disease4 and have continued to improve the transplantation process. A recent publication demonstrated the most advanced model where dopamine neural progenitor cells were transplanted in NHP models of Parkinson’s disease and were shown to reduce disease symptoms significantly with lower immune risk over a 2-year period⁵. As expected, autologous transplantation showed longer engraftment with low immune risk compared to allogeneic transplantation.

In summary, it is clear that NHP pluripotent stem cells have disease specific applications to evaluate advanced modalities such as cell therapies. It is likely that the next generation of NHP iPSCs will have improved reprogramming and differentiation efficiencies and NHP stem cells will have an important role in the translational drug development toolkit.

References:

¹https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349583/

²https://pubmed.ncbi.nlm.nih.gov/9804556/

³https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5951134/

⁴https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8848615/

⁵https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8198752/

29 | Feb | 2024

Chinese

Therapeutic antibodies have traditionally been developed via one of two method – phage display and transgenic mouse models. Both approaches have been shown to be successful as several antibody therapies are available commercially. Another method that is gaining interest is B cell screening but as of now, no approved antibody has been developed using this method. The first monoclonal antibody therapy was approved in 19861¹, and as of June 2022, 162 antibody-based therapies have been approved for commercial use². It is estimated that at least 23 marketing applications for antibody-based therapies will be submitted by the end of 2023 and this number includes 5 bispecifics and 2 ADCs (antibody-drug conjugates)³. Despite the clinical and commercial success of antibody-based therapies, there are challenges with the current methods that include high costs, long timelines and limited success with targets that have low immunogenicity. Additionally, it is difficult to target functional epitopes and it is important to note that strong binding may not be an indicator of function.

Antibody drug developers are increasingly turning to artificial intelligence (AI) based methods to improve process efficiency and quality of antibody candidates. Several companies are developing AI-powered workflows for antibody discovery. One such company is LabGenius based in the UK that combines automation, machine learning and disease-relevant readouts in an algorithm that identifies antibodies that can differentiate between a normal and disease state based on known readouts⁴. The process supports the identification of unexpected candidates as there is minimal human intervention and due to the automation and speed of the machine learning process, it takes about 6 weeks from start to finish⁴. Another example is a recent report from Xtalpi, a company based in China⁵ who used humanized mouse-generated antibodies as the input data to build AI models. The team combined a large antibody sequence dataset with an AI model that can predict pairing of antigen epitopes and antibody sequences thus reducing the time and costs associated with screening and identifying antibody candidates in mouse model⁵. Simply put, the AI driven workflow can accurately simulate a humanized mouse model for antibody development in a fraction of time and expense.

Recently, generative AI methods are being used to power antibody discovery. Generative AI is the method used to create language-based algorithms such as ChatGPT and uses patterns and structures from the input training data to create new data. In the antibody discovery space, generative AI can be used to design endless antibody combinations from large data sets that have been built from antibody campaigns⁶. The unique aspect of using generative AI is the zero shot concept where the algorithm can design new structures that it has not been trained on. This means that the zero shot method can be used to generate antibodies for new targets without requiring training data for that specific target. Given the power of this approach, it is not surprising that companies have adopted the generative AI approach for identifying novel therapeutic candidates including small molecule inhibitors and therapeutic antibodies⁷. Absci, an antibody discovery company, recently reported the identification of antibodies targeting human EGFR and Her2 using a combination approach of generative to AI to create close to 3 million design per week and high throughput screening to validate antibody candidates that bind to the target antigen⁸. This combination process eliminated several steps in the antibody development process including optimization of in silico candidates and time-consuming lead optimization studies.

As generative AI becomes integrated into antibody discovery workflows, it increases the probability of identifying novel antibody candidates for diseases that had complex pathophysiology or were deemed “undruggable”. If this potential is realized, then generative AI could completely transform the early-stage screening and identification of therapeutic candidates across multiple modalities.

References:

¹https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8664682/#

²https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9535261/#

³https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9728470/#

⁴https://www.wired.com/story/labgenius-antibody-factory-machine-learning/

⁵https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10370440/

⁶https://www.news-medical.net/news/20230111/Generative-AI-approach-unlocks-path-to-accelerated-antibody-drug-creation-for-novel-therapeutic-targets.aspx

⁷https://www.pharmaceutical-technology.com/comment/generative-ai-revolutionise-drug-discovery/

⁸https://www.biorxiv.org/content/10.1101/2023.01.08.523187v1

13 | Feb | 2024

Chinese

Preclinical toxicology studies are required for every therapeutic development program as these studies answer fundamental questions on the local and systemic effects of the test drug on the patient. Typically, tox studies are performed in small and large animal models and use defined endpoints. The guidance issued by the FDA has clearly stated the minimum requirements for preclinical toxicology studies include PK/PD profiling, acute toxicity studies in two species (rats and dogs are the most commonly used) and short-term toxicity studies to evaluate continued and potentially delayed onset adverse effects¹. Traditional toxicology studies have been more observational and record the ADME characteristics, biodistribution and PK/PD profiling along with optimal dose ranges that have acceptable off target effects. However, there is an increasing shift towards a more active investigational toxicology approach that can be either prospective or retrospective². Prospective investigative toxicology, as the name suggests, is performed during the discovery stage to quickly identify promising drug assets that have low toxicity and can move forward into efficacy evaluation. This approach supports the concept of “fail early and fail fast” so that assets with unacceptably high levels of toxicity are removed early from the development pipeline, thus saving significant time and downstream costs. These prospective studies are typically performed in translational in vitro models that range from simple 2D cell culture models and 3D organoids to highly complex microphysiological systems (MPS) such as organ-chips³. The retrospective approach is focused on understanding the mechanism of action of adverse effects identified in in vivo animal models or clinical trial patients. These studies can use multiomics-based approaches to review global changes in gene and protein expression profiles in response to drug exposure combined with ADME, histopathology and PK/PD data. The retrospective analysis is very useful to design next-generation therapies that can bypass the signaling triggers that cause off-target effects.

Prospective investigative toxicology studies are recently gaining traction due to the interest in responsible animal use and regulatory willingness to accept data generated in in vitro and ex vivo models. The FDA Modernization Act in the US and the activities by European medical agencies to promote animal-free testing has accelerated the development of complex in vitro model systems to predict toxic effects. It is important to note that in vitro model development has moved at different paces depending on the organ. For example, lung MPS model development was very rapid in response to the COVID-19 pandemic, while liver and kidney MPS development are moving at a slower pace in part due to tissue complexity. The availability of high-quality input materials impacts the pace of development – for example, researchers are dependent on hepatocellular carcinoma (HepG2) cells or primary hepatocytes to test therapies for drug induced liver injury (DILI), which is a critical tox readout. These models are not fully representative of the in vivo state and, in the case of primary hepatocytes, supply and quality continue to be issues. The development of reliable, high-quality iPSC-derived hepatocytes has been a challenge but as reprogramming technologies continue to improve, it is likely that this challenge will be solved. Another example is the development of translational complex kidney models. Simple 2D overexpression models have been used for several years to study drug-drug interactions (DDI) but the recapitulation of kidney glomeruli in vitro is a complex issue. Nephrons, the functional units of the kidney, consists of over 20 cell types that are arranged in a complex structure⁴ but MPS platforms typically use 2 cell types – epithelial cells and endothelial cells. Micro-physiological systems (MPS) for kidney cell culture were first reported in 2013 with the development of a kidney chip5 that showed expression of uptake and efflux transporters, resulting in accurate and reproducible responses to known transporter inhibitors such as cimetidine. Bioprinting is another technology that is being investigated to develop a 3D model of the kidney for the use in investigative toxicology studies⁴.

It is clear that the development of complex in vitro models for investigative toxicology is on an accelerated pace. As the development of input materials and culture systems continue to improve and evolve, the combination of biology and engineering will result in human in vitro systems that recapitulate the in vivo state to better predict off target effects.

References:

¹https://www.fda.gov/drugs/investigational-new-drug-ind-application/drug-development-and-review-definitions#

²https://www.nature.com/articles/s41573-022-00633-x

³https://www.altex.org/index.php/altex/article/download/1163/1280/6097

⁴https://portlandpress.com/essaysbiochem/article/65/3/587/228946/Bioprinting-of-kidney-in-vitro-models-cells

⁵https://pubmed.ncbi.nlm.nih.gov/23644926/

02 | Feb | 2024

Chinese

Imaging methodologies are critical in the diagnosis and prognostic monitoring of solid tumors in humans. Methods such as CT (computed tomography), MRI and PET are widely used in humans and these methods have continued to improve in terms of resolution, sensitivity and data analysis. More recently, the use of AI enablement was reported to improve detection of different solid tumors including skin, breast and head and neck¹. Additionally, the combination of different imaging modalities such as MRI and PET have been shown to increase accuracy of tumor detection¹. The use of imaging methods to noninvasively detect and monitor tumors in preclinical oncology animal models is becoming more widespread especially due to the translational value of the protocols, tracers and data analysis methods². Similar to humans, multi-modal preclinical imaging can be used to obtain data on various tumor characteristics including size, morphology, metabolic activity, vasculature and inflammation².

Preclinical imaging methods can be segmented into the following types: MRI, CT, ultrasound, photoacoustic (PAT) imaging, PET, SPECT and optical imaging (fluorescent and bioluminescent imaging)²,³. MRI is considered the gold standard of imaging modalities and has been shown to have the best tissue resolution that can be enhanced with specific tracers². Additionally, there are various subtypes of MRI that are tailored to measuring specific characteristics – for example, tissue oxygen levels can be measured via functional tissue oxygen-level dependent MRI that could be used to monitor response to radiotherapies². The use of contrast agents such as gadolinium chelate allow the visualization of changes in blood vessel architecture in tumors and there are ongoing studies to use gadolinium-based agents to identify cell surface receptors in tumor cells². Certain imaging methods are more suited for specific tissues types – for example, CT imaging is the optimal method to identify lung lesions due to excellent contrast between air and tissues². Clinically, ultrasound imaging is the method of choice to detect pancreatic cancers in both human and animal models. Preclinically, ultrasound is also sued used to guide orthotopic model development by helping researchers inject cells in the correct tissue space² and can be combined with PAT imaging to provide physiological data on the tumor. The basic principle of PAT imaging uses short laser pulses to irradiate tumor tissues leading to heat induced tissue expansion that creates acoustic waves⁴. The acoustic waves can be measured using ultrasound⁴.

PET imaging is used to monitor physiological changes in metabolic activity, vasculature etc. and uses radiolabeled tracers such as ¹⁸F-fludeoxyglucose (FDG) to monitor glucose uptake in tumors. Since tumors are more metabolically active than surrounding tissues, ¹⁸F-FDG PET imaging is a useful method to monitor tumor size and evaluate changes in tumor metabolism after therapeutic intervention5. While ¹⁸F-FDG is the most well-known tracer, PET imaging can be performed using multiple radiopharmaceutical tracers and some of the tracers can also be used for SPECT imaging which uses a gamma camera instead of a positron emission scanner. One of the key advantages of using PET and SPECT imaging is that radiolabeled tracers can be used to monitor specific reception expression levels or physiological markers². For example, ¹⁸F-fluorothymidine can be used to monitor DNA synthesis and cell proliferation in tumors. Given the huge focus in immune-oncology, “immuno-PET” has emerged as a specific imaging method where antibodies to select receptor targets or T-cell targeting molecules can be labeled with radiopharmaceutical tracers to monitor the response to specific checkpoint inhibitor therapies²,⁵. One such reported tracer is a ⁶⁴Cu-labeled Axl antibody that was used to monitor the efficacy of an hsp90 inhibitor (17-AAG) to downregulate Axl regulation in triple negative breast cancer⁶.

In vivo optical imaging methods such as fluorescent and bioluminescent require the insertion of a fluorescent tag or a luciferase enzyme into tumor cells or the therapeutic modality². The tags can be inserted into microbes, viruses, antibodies, peptides etc. so noninvasive luminescent imaging is an easy way to track tumor cells or therapeutic modalities in an animal model. While several fluorescent proteins are used in preclinical studies, one challenge is autofluorescence in specific tissues that can obscure or interfere with the fluorescent signal². Bioluminescent imaging using luciferase reporters has gained significant traction in preclinical in vivo studies and there is active research to engineer more sensitive luciferase enzymes that have more catalytic activity and improved emission signals⁷

References:

¹https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8945965/

²https://aacrjournals.org/cancerres/article/81/5/1189/649702/Preclinical-Applications-of-Multi-Platform-Imaging

³https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3687654/

⁴https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6515147/#

⁵https://www.itnonline.com/article/role-pet-imaging-preclinical-oncology

⁶https://pubmed.ncbi.nlm.nih.gov/29097911/

⁷https://pubs.acs.org/doi/10.1021/acschembio.1c00549

16 | Jan | 2024

Chinese

Lipid nanoparticles (LNPs) are vesicle composed of lipids that are used to deliver a wide range of therapeutic modalities including nucleic acids (DNA, mRNA, siRNA), antibiotics and small molecules (such as doxorubicin)¹. The most well-known application of LNP drug delivery are the mRNA COVID-19 vaccines developed by Pfizer/BioNTech and Moderna. Fundamentally, LNPs are spherical vesicles composed of ionizable lipids whose charge changes in response to pH². LNPs have neutral charge at physiological pH, which facilitates entry into cells but have positive charge at acidic pH to promote complex formation with negatively charged nucleic acids. LNPs are internalized into cells via endocytosis and release the payload in the cytoplasm upon exposure to low pH². LNPs can take various forms including liposomes, nano-emulsions, solid lipid nanoparticles, nanostructured lipid carriers, and lipid polymer hybrid nanoparticles¹. Liposomes are best known for delivering chemotherapies such as doxorubicin and paclitaxel for cancer treatment and lipid polymer hybrid particles have also been used to deliver docetaxel for treatment of various cancers1. The nanostructured lipid carriers and solid nanoparticles have been used to deliver nucleic acid therapies. Apart from therapies, LNPs are gaining interest in cosmeceuticals which is an unregulated space that primarily consists of skin and hair care products³. LNPs have desirable properties for topical applications as they adhere well to the skin and easily disperse across the tissues. However, since this space is not overseen by regulatory agencies like the FDA or EMA³, it is important for manufacturers to manufacture and test the LNPs to ensure high quality standards.

Various types of LNPs have been used to deliver different therapeutics, antibiotics and sedatives since the 1990s. A majority of the therapies use liposomes⁴, and the first LNP based siRNA (Patisiran) therapy was approved in 2018 for the treatment of hereditary transthyretin amyloidosis². The mRNA based COVID-19 vaccines that were approved in 2021 also used LNPs to deliver mRNA targeting the spike protein of the SARS-CoV2 virus. However, it is important to note that LNPs have pros and cons. One of the key advantages of LNPs is the low toxicity rate since the lipids are biocompatible and do not trigger significant toxicity. Structurally, LNPs are very stable and are amenable to tissue targeting. Depending on the target tissue or organ, LNPs can be directly administered via nebulization to the lung or direct injection into the eye⁵. LNPs have natural tropism to the liver so they are well-suited to target hepatic diseases and this property is being used to engineer LNPs to deliver payloads to the liver at high efficiency. Additionally, LNPs can be targeted to immune cells such as T-cells via specific antibodies such as anti-CD4⁵. Currently, there is active research to develop next-generation LNPs that have specific tissue targeting properties. LNPs also have certain disadvantages and the major challenge is the low drug loading and delivery efficiency. While this is not a major issue for vaccines, it is of concern to deliver drugs in sufficient quantity to exert a therapeutic effect. LNPs also have short blood circulation time and are susceptible to removal by macrophages causing a low number of LNPs reaching the target tissues. While LNPs are considered to be the most clinically advanced nonviral gene delivery method, the current status of the field restricts LNP use to specific applications but the fields of use are likely to grow with improved next-gen LNPs.

References:

¹https://pubs.acs.org/doi/10.1021/acsmaterialsau.3c00032

²https://www.nature.com/articles/s41578-021-00281-4

³https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8864531/

⁴https://www.biochempeg.com/article/283.html

⁵https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9322927/

04 | Dec | 2023

Chinese

Antibody drug conjugates (ADCs) are targeted therapies that consist of a monoclonal antibody (mAb) linked to a chemotherapeutic via a linker. The mAb binds to a target receptor antigen on tumor cells and the ADC complex is internalized into tumor cells resulting in the release of a chemotherapeutic drug that kills tumor cells. The main advantages of developing an ADC are low off target effects and an expanded therapeutic index of the chemotherapy resulting in more effective tumor killing. The concept of using a mAb to deliver a cytotoxic payload to tumor cells is not new but early attempts to develop clinically effective ADCs were unsuccessful due to a few reasons such as poor linkage resulting in separation of the payload, off-target toxicity due to nonspecific antibody binding, immune responses resulting in rapid clearance and low residency time etc¹. Additionally, ADCs can be developed against specific membrane bound receptors that have an antigenic extracellular domain that does not get released or shed into the extracellular environment or vasculature¹. ADC targets are typically overexpressed in tumor cells compared to normal cells so the continued discovery of differentially expressed biomarkers will help the development of novel ADCs. Currently, most ADCs target receptors or ion channels that are difficult antigen targets, but improvements in antibody discovery methods have helped improve the quality of therapeutics antibodies used in ADCs.

Another critical element of developing an ADC is the linker technology. Using a weak or incorrect linker could result in early release of the payload causing systemic toxicity or cause aggregation of the ADC complexes². Currently, there are 2 classes of linkers – cleavable and non-cleavable³. Cleavable linkers are primarily cleaved in one of 3 ways – protease, reduced pH or in the presence of reduced glutathione²,³. Enzyme mediated linker cleavage is commonly used and about two-thirds of approved ADCs employ this appriach². Non-cleavable linkers typically fall in 2 categories – thioether and maleimidocaproyl and are generally considered to be superior to cleavable linkers³. ADCs with non-cleavable linkers are dependent on cellular lysosomal degradation so release of the chemotherapeutic agent only occurs in tumor cells. Therefore, ADCs with non-cleavable linkers have more stability in the vasculature and have a larger therapeutic index and there is active research to develop new and improved linkers.

ADC payloads have historically been available chemotherapies that inhibit cell proliferation, but recently, novel payloads have been used. One example is Enhertu whose payload is a topoisomerase I inhibitor that can inhibit DNA replication in tumor cells⁴. Another example is Lumoxiti, an ADC targeting hairy cell leukemia whose payload is a Pseudomonas exotoxin A⁴. Lumoxiti has been recently discontinued due to low market uptake but is an example of creative payload design.

Currently, there are 11 approved ADCs in the US and over 150 ADCs in clinical trials⁵. 2 ADCs (Mylotarg™ and Blenrep™ were discontinued due to failure to meet endpoints in post-marketing approval clinical trials but Mylotarg was re-approved at a lower dose⁵. Due to the clinical success of ADCs, biopharma companies are investing significantly in the space leading to the renaissance of ADCs⁶. Several large pharma companies such as Pfizer and Astra Zeneca have announced large acquisition or ADC asset deals signaling that pharma companies are interested in developing and commercializing ADCs⁶. There are a couple of major reasons why pharma is interested in ADC assets. The ADC technology platforms have improved significantly and the current third generation of ADCs demonstrate high target specificity while evading the immune system. Additionally, newer ADCs with superior linker technology can carry more payload. One example of a superior ADC is Enhertu that was approved in December 2019 for HER2-positive metastatic breast cancer⁶ that has a drug antibody ratio or DAR of 8. The Phase III clinical trial data for Enhertu showed a stunning 72% reduction in disease progression⁶ and was a major clinical success. From an economic point of view, ADCs are difficult therapies to develop biosimilars due to the multiple components, so ADC developers have a longer window to generate revenue and have more pricing power⁶.

Given the technological advancements in monoclonal antibody development, linker chemistry and payloads along with a track record of clinical success and high barrier to entry for biosimilars, there is no doubt that ADCs are experiencing a true renaissance and this is positive news for many cancer patients with limited therapeutic options.

References:

¹https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359697/

²https://www.biochempeg.com/article/87.html

³https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628511/

⁴https://ascopubs.org/doi/full/10.1200/EDBK_281107

⁵https://pubmed.ncbi.nlm.nih.gov/37639687/

⁶https://www.biospace.com/article/biopharma-bets-big-on-antibody-drug-conjugates/

15 | Nov | 2023

Chinese

The drug development and manufacturing industry in China has historically focused on generic drugs and Chinese CROs have heavily depended on drug development business from Western countries. However, these trends have changed significantly in the past several years, and it is becoming clear that the biopharma sector in China is growing rapidly with a focus on technology innovation and first-in-class drugs. This change started in 2015, when China’s regulatory agency, the National Medical Products Administration (NMPA), started a series of reforms and changes to accelerate in-country drug development and expand clinical trials ¹. One of the key reforms was the decoupling of drug development and production where the drug developer does not have to be the drug manufacturer². This decoupling allows companies to focus on innovative drug discovery without the need to divert resources to process development, scale up manufacturing, quality control and lot release of the drug product. Secondly, the Center for Drug Evaluation (CDE) issued guidelines for conducting clinical trials across multiple therapeutic areas including oncology and rare diseases², thus encouraging more in-country trials of novel therapies. Additionally, the funding environment to support Chinese biopharma companies has grown significantly in the past several years. There has been a rapid increase of available capital through VC firms and more relaxed regulations for companies to go public including the formation of the STAR Board³ in Shanghai.

Notably, in 2023 there have been several licensing deals where Chinese biotech companies have developed and licensed drug assets to big pharma and conversely, have in-licensed several drug assets⁴. This bidirectional licensing activities suggests that Chinese biopharma companies have gained traction on the world stage as developers of high-quality therapeutic assets. Licensees include top pharma companies such as GSK, Takeda and AstraZeneca and the total value of the top 10 licensing deals range from $2 billion to $700 million⁴. However, the deals where Chinese biotech are the licensees tend to have a lower total value and range across multiple disease areas including oncology, infectious disease and liver disease⁴. Unsurprisingly, as the number of biotechs developing licensable assets increases, China based CROs are also growing likely to accommodate the increased outsourcing needs.

The 2022 top global CROs list includes 3 Chinese companies – Wuxi AppTec, Pharmaron, and AsymChem⁵. The revenue growth projections of China based CROs continues to be strong with an anticipated market growth 13% in 2021 to 19% in 2024⁵. While China based CROs have always been known to have deep expertise in chemistry and small molecule drug development, in the past few years there has been a rapid growth in advanced modalities including monoclonal antibody-based therapies. Importantly, the CROs are no longer dependent on business from North America and Europe since Chinese biopharma companies are outsourcing to in-country CROs. This trend likely started during the COVID-19 pandemic but has continued to hold strong as Chinese CROs have developed impressive end-to-end capabilities across the drug discovery continuum. It is estimated that about 40% of WuXi Biologics, a leading Chinese CRO, client base is in country⁶. Another key development has been that China joined the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use in 2017, allowing the use of data from clinical trials run in China to be used in filings to multiple regulatory agencies⁶. Since this development, the clinical CROs based in China can compete with global clinical CROs as they can generate usable data at a more economical price tag compared to several North American and European CROs⁶.

It is clear that China continues to be a competitive player in the preclinical and clinical drug development sector and is expected to grow at a significant pace. This growth is fueled by available capital, supportive government regulations, lucrative licensing deals and an aggressive strategy from Chinese CROs to support domestic biopharma companies while penetrating Western markets.

References:

¹https://globalforum.diaglobal.org/issue/june-2021/chinas-new-era-of-reform-transforming-regulatory-professionals/

²https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10326289/

³https://www.pharmexec.com/view/china-invests-in-building-biotech

⁴https://baipharm.chemlinked.com/news/2022s-top-10-cross-border-licensing-deals-involving-chinese-biopharma-companies

⁵https://baipharm.chemlinked.com/news/china-contract-research-organization-cro-2022-review-and-outlook

⁶https://www.spglobal.com/marketintelligence/en/news-insights/latest-news-headlines/chinese-drug-contract-research-companies-see-surge-in-domestic-demand-63832298

06 | Nov | 2023

Chinese

The drug development pipeline is increasingly moving towards complex therapies such as monoclonal antibodies and their derivatives, cell and gene therapies and nucleic acid (DNA and RNA) therapies. The critical requirement to support clinical trials and successful commercialization of advanced therapies is high quality consistent manufacturing that is primarily outsourced by pharma to CDMOs (contract development and manufacturing organization). The rapid growth in the complex therapies pipeline has fueled the need for manufacturing capacity at CDMOs that is supported by experienced talent and establishing quality systems. Not surprisingly, the pharmaceutical CDMO market is experiencing high growth with a current marker size of $95B in 2022 that is expected to grow to over $170B in a decade with an estimated 6.2% CAGR¹. While estimated market sizes do vary across reports, most reports suggest that the CDMO market is expected to double in the next decade or so.

Historically, drug developers have been primarily based in North America and Europe (NA and EU) who have partnered with CDMOs in the same geographies². This has largely been due to the interest in building and maintaining a close bond between drug developers and CDMOs. CDMOs in North America and Europe have had access to premier talent pools and manufacturing expertise across multiple advanced modalities. It is estimated that about 37% of CDMOs have comprehensive end-to-end portfolios², which, helps foster strategic partnerships with drug developers. However, a survey in 2014 revealed an interesting trend that drug developers did not consider geographic location to be a key consideration for selecting a CDMO³ suggesting that the CDMO globalization trend was only a matter of time.

The dominant position of North America and European CDMOs is being challenged by an increasing trend towards globalization especially in Asia. There are a few key reasons for this globalization trend – capacity, supply chain and expertise. Drug developers are increasingly concerned about a “capacity crunch” at NA and EU CDMOs that can delay manufacturing and negatively impact the race to be first to market⁴. This has led to drug developers towards CDMOs in China and India that have available capacity. Additionally, the COVID-19 pandemic had a significant impact on supply chain availabilities and costs of raw materials and consumables resulting in large price increases and manufacturing delays⁵. The rush towards manufacturing COVID-19 vaccines and antiviral therapies has helped equip several Asia based CDMOs with the infrastructure and knowhow to manufacture advanced biologics and complex therapies at a high quality.

Specifically, China is experiencing extremely high growth in the CDMO sector at an estimated 32% CAGR⁶. One of the major reasons that triggered this growth is a legislative change in 2015 where Chinese drug developers did not have to build in-house manufacturing facilities and could use CDMOs to manufacture drugs for approval⁶. This allowed the CDMO sector to grow rapidly and develop advanced capabilities to manufacture biologics therapies. India is another growing CDMO geography and this is largely being fueled by low costs and the availability of skilled labor⁶. Other emerging geographies for CDMO outsourcing include Latin America and Africa but these seem to be initially focused on vaccine production.

An interesting trend that is being observed is the shift of Asian CDMOs to North America and Europe. Several savvy CDMOs that were originally based in Asia (primarily China) are recognizing the need to have a presence in drug development hubs in the US and other countries. This shift is helping increase the profiles of CDMOs that originated in Asia but are now global organizations with end-to-end capabilities to support drug development and manufacturing globally. As this trend increases, it is clear that the CDMO world will move towards a virtual global space where physical distances are irrelevant and drug developers will have a broad range of global CDMO partners to accelerate advanced therapies to market.

References:

¹https://www.globenewswire.com/en/news-release/2023/06/07/2683991/0/en/Pharmaceutical-CDMO-Market-Size-Will-Expand-to-USD-172-02-BN-by-2032.html

²https://www.strategyand.pwc.com/de/en/industries/health/2022-global-cdmo-study.html

³https://www.pharmtech.com/view/biomanufacturing-outsourcing-globalization-continues

⁴https://www.bioprocessonline.com/doc/top-trends-in-biomanufacturing-for-0001

⁵https://www.bioprocessonline.com/doc/s-bioprocessing-year-in-review-key-takeaways-0001

⁶https://www.cphi-online.com/emerging-regional-markets-show-promise-as-cdmo-news114072.html

13 | Oct | 2023

Chinese

The drug development process has several critical milestones. One of the milestones is pharmacokinetics (PK) studies, which is the study of how a given drug interacts with the body. PK studies typically evaluate the ADME or absorption, distribution, metabolism and excretion of a new therapy. Crossing the BBB poses a significant challenge for several therapies that target brain diseases including neurodegenerative diseases and brain tumors. PK studies performed in the CNS are especially important to ascertain how much of a given drug crosses the blood brain barrier (BBB)¹ to have a therapeutic effect on brain tissues. If the drug cannot cross the BBB efficiently, then it is likely to have limited therapeutic efficacy at an acceptable dosage. It is important to understand the barriers between blood, CSF and the extracellular fluid (ECF) to appreciate the complexities of drug transport into the brain. The BBB separates blood flow from brain tissue and is a tight barrier with no gap junctions or pores, while the BCSFB (blood CSF barrier) is more porous and supports vesicular pinocytosis for the transport of biomolecules including drugs². Since CSF freely interacts with blood and is in fact produced from blood plasma, drugs that are administered systemically are detected in CSF². CSF can deliver drugs to specific areas of the brain³. The most common administration methods are lumbar puncture and ICV or intracerebroventricular injection³. Measurement of the available drug concentration and metabolites in CSF after administration are typical readouts to assess ADME characteristics.

Typically, PK studies are performed in primate models that have similar brain anatomy and physiology as humans. PK studies are complex and require analysis at multiple time points to map out the effect of the drug on the body, so it is essential to use minimally invasive methods for repeated sampling of biofluids. There are a couple of different methods to access biofluids in the CNS. One approach is CSF sampling through lumbar puncture or through the cisterna magna, and another approach is through microdialysis where a probe is placed in the tissue of interest to facilitate sampling⁴. Both approaches have their uses and limitations. CSF sampling typically uses lumbar puncture for repeated sampling of the spinal CSF, while microdialysis samples ECF around the tissue of interest⁴. Secondly, microdialysis is more widely performed in rodent models with limited use in nonhuman primates, while CSF sampling is well established in nonhuman primates. Microdialysis methods are useful to analyze the immediate environment surrounding a brain tumor or brain region of interest while CSF sampling provides a more global picture of free or unbound drug concentrations. Typically, samples from a microdialysis probe are used to evaluate changes in secreted proteins and neurotransmitters and locally expressed biomarkers. On the other hand, CSF sampling can be used to evaluate global biomarker changes as the sampling is typically done at a site that is distal to the tissue of interest. Interestingly, some reports have shown no significant differences in drug PK characteristics between CSF samples and ECF samples acquired through microdialysis⁵. Therefore, it is important to select the appropriate sampling method depending on the experiment objective and animal model of choice. In summary, sampling and analyzing the CSF are essential to evaluate both direct drug delivery and drug pharmacokinetics in the CNS.

References:

¹https://pubmed.ncbi.nlm.nih.gov/15381336/

²https://link.springer.com/article/10.1007/s10928-013-9301-9

³https://www.sciencedirect.com/science/article/pii/S0169409X21000685

⁴https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6388052/

⁵https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4151035/

02 | Oct | 2023

Chinese

CNS (central nervous system) tumors are primarily located in the brain with some tumors in the spinal cord. CNS tumors can be of various types and are typically named for the cells that are involved – for example, astrocytomas are tumors growing in astrocytes¹. Globally, over 308,000 people are estimated to be diagnosed with a CNS tumor and about 25,000 adults in the US are expected to be diagnosed per year². Additionally, over 4,000 children are diagnosed with a brain tumor and most cases have a poor prognosis². Given the limited therapeutic options for CNS tumors, early and accurate diagnosis of tumors is critical to improve prognosis and survival rates.

Accessing the brain tissue directly is complicated and invasive but the cerebrospinal fluid (CSF) is a viable alternative to assess cancer biomarkers. CSF is a body fluid that circulates over the brain and down the spinal cord. Since it comes into contact with brain tissue and tumors, secreted biomolecules or cancer cells diffuse into the CSF and can be detected using established analytical or cell based assays³. CSF sampling is typically done using a lumbar puncture where a needle is inserted into the spinal cord between the vertebrae. However, cancer cells and secreted biomarkers are not typically found in abundance in the CSF and the analysis may not always be reliable. Therefore, there is a need for more sensitive assays to identify low abundance biomarkers or cancer cells³.

Current assays to identify cancer cells include cytology analysis where CSF samples are analyzed under a microscope, and flow cytometry analysis to identify cancer cell surface markers. A few recent studies have demonstrated that circulating tumor cells (CTCs) in the CSF can be detected used the FDA approved CellSearch® system⁴. The CellSearch system was originally approved to detect CTCs in breast, colorectal and prostate cancer⁵, but it has also been successfully used to identify CTCs in breast cancer related brain metastases⁶. It is likely that as more studies with larger patient cohorts are performed, CTC detection in the CSF may become a standard diagnostic tool to identify brain metastases as well as CNS tumors.

CSF samples are rich in different biomarkers that are typically proteins or microRNAs. Changes in protein composition in CSF from normal vs cancer patients can be measured using ELISA or IHC based assays as well as proteomic analysis or mass spectrometry. A study in 2006 used a mass spectrometry-based method to identify elevated levels of carbonic anhydrase as a marker for gliomas⁶. Several studies have compared normal and malignant patient samples and have identified levels of specific markers³. While the results of these studies show promise, it will be important to thoroughly validate tumor type specific biomarkers to meet regulatory requirements for diagnostic testing. MicroRNAs (miRs) are short noncoding RNA fragments that bind to the 3’ end of mRNA and inhibit protein translation. There has been an explosion of interest in developing miR based therapies and several miRs have been identified as high potential drugs for specific tumor types. However, as of now, no miR based therapies have been approved by the FDA but the interest in the biopharma industry continues to grow. Identifying miRs in CSF samples is of high interest as diagnostic biomarkers especially since panels of miRs can be used to diagnose specific CNS tumor types. An example of this panel type approach was reported in 2012 where 7 miRs were used to accurately identify glioblastoma and metastatic brain cancer⁷.

References:

¹https://www.mayoclinic.org/diseases-conditions/brain-tumor/symptoms-causes/syc-20350084

²https://www.cancer.net/cancer-types/brain-tumor/statistics#

³https://jcmtjournal.com/article/view/1321

⁴https://academic.oup.com/clinchem/article/68/10/1311/6661459

⁵https://www.cellsearchctc.com/

⁶https://pubmed.ncbi.nlm.nih.gov/17078017/

⁶https://pubmed.ncbi.nlm.nih.gov/22492962/