Background
In vitro diagnostics (IVD) are a vital component of the biopharmaceutical industry, boasting a highly cost-effective industry. Retaining only 3% of medical resources, the IVD industry holds over 70% of clinical decision-making power. It serves as the primary basis for clinicians formulating treatment plans and represents the largest market segment within the medical device industry. Due to the impact of the COVID-19 pandemic, China's IVD market has experienced explosive growth in the past two years. The upstream IVD industry holds strategic importance within the entire IVD supply chain. Antigens and antibodies are the source of diagnostic technology innovation, and the dominant position of raw materials determines the cost-effectiveness of IVD systems and represents a bottleneck to industry development.
Currently, there are multiple methods for screening diagnostic antibodies, but each technology has its limitations, such as the variability and difficulty of serum-based acquisition, the lengthy and difficult development of hybridoma-derived antibodies, the potential limitations of sequence and epitope diversity due to immune bias in phage display technology, and the expensive screening of single B cells. Researchers have found that protein mass spectrometry sequencing offers faster acquisition times and lower costs, and is considered a shortcut by diagnostic companies, impacting traditional antibody development. However, in the development of diagnostic antibodies, differences in downstream assay methodologies and the impact of constant regions outside the core of the antibody variable region are often overlooked.
On June 25, 2024, Professor Wang Zhanhui's team at China Agricultural University published an article titled "The Challenges and Breakthroughs in the Development of Diagnostic Monoclonal Antibodies" in VIEW. The article provides an in-depth analysis of the challenges facing in vitro diagnostics (IVDs) and proposes innovative strategies for the development of next-generation diagnostic antibodies. These strategies aim to achieve a closer approach to the gold standard for antibody discovery and enhance the competitiveness of diagnostic reagent products.
Antibody discovery
Antibodies were first discovered in 1890 by German scientists in mice injected with serum from rabbits infected with tetanus. At the time, scientists discovered the presence of cell-free immunoreactive substances in the serum: antitoxins, now known in the biomedical field as antibodies. It was subsequently confirmed that antibodies are a class of proteins with the ability to specifically bind to invading substances. The structure of antibodies was then elucidated, along with the principles of antibody genetic diversity. The discovery of antibodies can be divided into three major phases: the first, the serum theory, which identified antibodies in serum; the second, the immune cell theory, which established the theoretical basis for antibody production by B cells; and the third, the genetic diversity theory, which elucidated the process by which antibody genetic material is produced. Based on these theories, antibody acquisition methodologies have been developed one after another, including obtaining antibodies through serum methods; fusing antibody-producing B cells with continuously proliferating myeloma cells through hybridoma technology to produce monoclonal antibodies with the same specificity; deeply discovering genetic material through phage display technology and combining it with recombinant protein expression for reproduction. This method can obtain high-affinity and high-specificity monoclonal antibodies, which are of great significance for molecular recognition and disease treatment in life sciences; and the currently booming single B cell screening combined with single cell sequencing technology. After animal immunization, the spleen, lymphatic system and peripheral blood generally contain B cells that can secrete single antibodies. This technology can screen out B cells that can effectively secrete target antibodies and obtain antibody gene sequences from their genetic material.
In addition, with the advancement of mass spectrometry technology, protein amino acid sequencing can bypass single B cells and, from a targeting perspective, enrich effective antibodies against antigens from serum, and use mass spectrometry technology to obtain the protein sequence of the target antibody, thereby obtaining candidate target antibodies.
Analysis of diagnostic antibody R&D issues
Issues in the animal immunization stage:
The design and production of immunogens during antibody production plays a crucial role in determining the effectiveness of the immune response. Therefore, from the perspective of immunogen acquisition, the following challenges exist: Replication of the antigenic target is difficult, especially for membrane proteins, resulting in long expression cycles and high development costs. Immunogenic proteins are primarily sourced from two sources: natural extraction and recombinant proteins. Natural extraction can only yield proteins with limited immunogenicity. For most projects, immunogens rely primarily on recombinant proteins. Designing recombinant proteins requires analysis of protein structure and physicochemical properties to select structural or linear epitopes. Furthermore, some antigenic proteins are extremely unstable and require specific formulations for storage. As immunogens, even the slightest misalignment can lead to conformational changes, making it impossible to obtain antibodies with good specificity for the true antigen. Achieving accurate reproduction of immunogenic proteins is currently a major challenge in screening for high-quality diagnostic antibodies. Immunogenic efficiency needs to be improved. With the increasing demand for precise detection of clinical biomarkers, the requirements for diagnostic antibody raw materials are moving beyond simple antigen recognition to include high affinity and high linearity.
Antibody screening system issues:
The discovery and development of monoclonal antibodies has gone through three stages, namely hybridoma technology, phage display technology, and single B cell screening technology, but each technology has its limitations.
Hybridoma technology: Its cycle is relatively long, requiring 4-6 months without animal immunization. Due to the low success rate of PEG fusion, with a positive screening rate of approximately one percent, alternative methods such as electroporation, Sendai virus, or other viruses are used to improve the efficiency of hybridoma fusion. In addition, due to the high proportion of chromosomal instability components in hybridoma cells and the presence of some hybridomas with low antibody production, they are not suitable for long-term effective use in GMP-grade bioreactors. Moreover, in the early stages of culture, some low-yield clones may grow faster than high-yield clones, resulting in their exclusion during molecular monoclonal screening. The preparation of antibodies from ascites requires the establishment of large animal facilities, which have high operating costs and may also raise ethical issues related to animal welfare in the future.
Phage display technology: The length of protein peptides that can be displayed on the phage surface is limited. Traditional Y-shaped antibody screening can only display the scFv portion, making it difficult to obtain naturally paired heavy and light chain combinations. Obtaining valid antibody sequences from B cells using phage display technology generally requires 3-5 rounds of screening, and the limitations of designed primers make it impossible to effectively obtain all valid antibody sequences. Furthermore, the screening process requires repeated washing, which places a heavy burden on the experimenter's time and energy.
Single B cell screening technology: High-throughput single B cell screening presents certain challenges. After obtaining hundreds or even thousands of candidate antibody sequences, scoring and ranking these sequences and identifying the optimal antibody or antibody combination requires extensive recombinant expression and validation. Furthermore, screening based on this type of pore separation technology and subsequent expression validation poses significant challenges to R&D costs.
Antibody expression reproducibility issues
Heterologous protein expression systems have limitations: the Escherichia coli expression system is not suitable for expressing complete antibody molecules and can only express single-chain antibodies or antibody fragments; although yeast, insects and plants also have post-translational modification functions similar to glycosylation, compared with human or mammalian eukaryotic cells, these cells have different glycosylation patterns, and the quality of the recombinant antibodies they express is quite different from that of natural human antibodies. Only mammalian cells are suitable for expressing heterologous human antibodies.
Constructing high-yield cell lines presents challenges: Currently, engineered cell lines used for recombinant antibody production can achieve expression levels of 20 to 70 pg/cell/day. Cell line growth and expression capacity are being enhanced through cell engineering, site-specific integration, and high-throughput screening. Genomic analysis has shown that the expression capacity of high-yield cell lines is the result of the synergistic interaction of multiple cellular properties, including energy metabolism, redox state, growth capacity, and protein processing capabilities.
Diagnostic antibody structural design requires further exploration: Nearly 95% of diagnostic raw material companies focus primarily on replicating complete antibody gene sequences, without fully considering the structural differences in antibodies and their subsequent impact on downstream reagents. The role of the antibody Fc region and the induction of the human anti-mouse antibody (HAMA) effect require further investigation. Questions remain regarding the potential benefits of a conceptual framework that reconfigures and rearranges the Fv, CH1 (CL), hinge, CH2, and CH3 regions of traditional IgG antibodies to achieve diversification.
Challenges and exploration strategies for diagnostic monoclonal antibodies
In response to some of the above technical challenges, researchers have proposed and fully implemented a pioneering development method for a new generation of diagnostic monoclonal antibodies.
RNA Immunity: The emergence of RNA vaccines, which utilize the viral genetic code to "trick" human cells into producing proteins identical to those on the surface of pathogens, offers unparalleled advantages in rapidly responding to outbreaks of new infectious diseases. The RNA vaccine model not only effectively addresses the problem of obtaining complex immunogens, but also enhances the original conformation of the immunogen by bypassing traditional immunogen replication or purification steps, theoretically improving the effectiveness of the immune response. From a cost perspective, this approach significantly shortens the development cycle and reduces the costs associated with immunogen acquisition.
Computer simulation technology: After obtaining a large number of candidate antibody sequences, computational antibody platforms are used to simulate the binding sites and affinity rankings of candidate antibodies to antigens, allowing the precise selection of dozens of optimal diagnostic antibodies from hundreds to thousands of candidate antibodies. This approach significantly reduces the throughput and cost of replication, providing a promising path for the integration of biotechnology and computer information technology (BTIT) to complete the final piece of the puzzle for high-throughput antibody development for single B cells.
Modular Customization of Diagnostic Antibodies: Therapeutic antibodies have demonstrated a variety of rationally designed structures, such as nanobodies, bispecific antibodies, trivalent antibodies, and tetravalent antibodies, while diagnostic antibodies only encompass a small subset of nanobodies and Fab antibodies. With the demand for streamlined processes and the emergence of new methods, modular customization of antibodies is an inevitable trend. Systematically organizing and researching modular antibody design will be crucial for the targeted loading of drug molecules/nucleic acids in ADCs/AOCs and the high-abundance loading of antibodies in ACCs. The emergence of new methods in the future will undoubtedly require greater diversity in antibody structure, providing significant opportunities for advancements in diagnostic antibody and biopharmaceutical development.
The pros and cons of protein sequencing technology
Advantages of protein sequencing: There are two main types of protein sequencing: Edman degradation sequencing and mass spectrometry-based protein sequencing. Edman sequencing does not require a protein database and can directly analyze amino acid information. This is particularly important for characterizing the N-termini of proteins, starting from the free α-amino group. However, Edman sequencing has limitations in sequence length and the availability of free α-amino groups. Mass spectrometry-based protein sequencing has made significant progress in protein sequencing from the N-terminus. Mass spectrometry sequencing can systematically decompose peptides to determine the complete protein sequence, including post-translational modifications. This provides a potential solution for sequencing polyclonal antibodies from animal serum, bypassing the tedious and expensive process of screening single B cells or effective genetic material. Obtaining sequence information directly from the termini significantly shortens the development cycle, revolutionizing the development of diagnostic antibodies and, by extension, therapeutic antibodies. Protein sequencing technology can be used to rapidly sequence neutralizing antibodies against the novel coronavirus, providing new insights into diagnostic antibody development. Combining protein sequencing technology with computer-aided antibody design platforms can precisely screen for optimal monoclonal antibodies from a large pool of polyclonal antibody sequences.
Disadvantages of protein sequencing: Due to the imperfect intellectual property system for diagnostic antibodies and the low consumption and complexity of antibodies in IVD reagents, many IVD manufacturers have shifted from the original forward development or outsourcing of diagnostic antibodies to global antibody analysis tests based on de novo protein sequencing technology. Reverse development and replication based on protein sequencing technology may seriously undermine the enthusiasm for forward development of diagnostic antibodies, leading to slow development of the entire industry.
Summary and Outlook
Currently, the main methods for antibody screening include hybridoma technology, phage display technology, and single B cell screening. The most critical step in the development of diagnostic and even therapeutic antibodies lies in antibody sequence discovery. The maturity of antibody mass spectrometry sequencing technology means that researchers can bypass the tedious antibody sequence discovery process, such as animal immunization and cell-based screening. New antibody sequences can be generated using only historical antibody-antigen data, servers, and algorithms. With the maturity and commercialization of protein mass spectrometry sequencing technology, its relatively short sequence acquisition time and significantly lower sequencing costs compared to forward development have led more diagnostic companies to view it as a shortcut for antibody development. However, it must be used judiciously. While the overuse of reverse antibody development may bring short-term profits to the diagnostic antibody industry, it will ultimately lead to slow or even stagnant development of the entire field. We need to redefine the structure of diagnostic antibodies, analyze the methodology of antibodies in diagnostics from an antibody structure perspective, and further refine antibody design. This is crucial for improving the performance of diagnostic reagents and is an indispensable stage in the future development of diagnostic antibodies. Currently, the development of diagnostic antibodies requires an organic combination of original theoretical innovation and cutting-edge technological breakthroughs. Specifically, this requires the synergy between novel immune mechanisms and high-throughput screening technologies, the establishment of computational antibody platforms, and the integration of new methods with antibody structural mechanistic research. Strategic positioning of AI-generated antibody platforms has also been identified as one of the effective ways to maintain industry leadership in diagnostic antibody development.
