Source: Future Industry Research Center, Westlake University

Not long ago, the Future Industry Research Center of Westlake University released the "Future Industry Development Trend Research 2023: Future Biomedicine". The report uses artificial intelligence text analysis technology to conduct data mining and analysis of global biomedical technology, identifies the key directions of the future development of China's biomedical industry, and puts forward a series of targeted policy recommendations.

Based on the global future biomedical industry layout and China's key research directions, combined with the current situation facing the development of China's future biomedical industry from 2035, and on the basis of fully considering the answers of the experts in the expert questionnaire to the open questions (what do you think are the future development directions and potential technology fields worth paying attention to), Explore ten areas that need to be focused on and strongly supported by China's future biomedical industry (in no particular order)

1. Field 1: Application of information technology such as artificial intelligence in biomedicine

The deep application of information technology such as Artificial Intelligence in the field of Biomedicine, namely "Artificial Intelligence + Biomedicine", refers to the enterprises and research institutions through the combination of artificial intelligence and biomedicine to achieve innovative breakthroughs in the field of biomedicine.

Artificial Intelligence (AI) is one of the key technologies in the world, and its research topics include computer vision, natural language processing, robotics, expert systems, recommendation systems, etc. Today, with the continuous breakthrough and rapid iteration of scientific and technological development, the cross-integration of different disciplines and fields in all walks of life to carry out deep innovation has become a new industrial development and scientific research paradigm. Biomedicine is a key cross-cutting research and application field of artificial intelligence. In 2017, Nature reported an AI system with expert skin cancer diagnosis capabilities [1], a groundbreaking milestone in AI-enabled biomedicine. In 2020, DeepMind released the AI algorithm AlphaFold 2, which can accurately predict the 3D structure of proteins based on amino acid sequences, and its accuracy is comparable to the 3D structure analyzed by experimental techniques. The achievement is considered to have solved a major challenge in biology for 50 years, triggered a shock in the scientific community, and once again set off a boom in the research and industrialization of "artificial intelligence + biological medicine". In 2022, Meta's ESMFold, based on the latest geometric deep learning model "EquiBind," successfully predicted the structure of more than 600 million proteins 60 times faster than AlphaFold 2.

"Ai + biomedicine" has been applied in many subfields of biomedicine (new drug development, enzyme and protein design, medical image analysis, disease prediction, disease prevention, intelligent diagnosis, precision medicine, etc.), and is expected to widely reshape the status quo of biomedical research and industry. "Artificial intelligence + biomedicine" can be put into use in the biomedical industry from upstream to downstream, and some application scenarios have been able to bring actual benefits to enterprises. Take new drug development as an example: in the research and research stage, "artificial intelligence + biomedicine" can extract key information related to drug research and development through automated text analysis of information from literature, etc., to assist R&D personnel in decision-making in research and industrialization; In the drug development stage, through the intelligent analysis of biomedical trials and clinical big data to shorten the cycle of discovering new therapeutic targets and new drug molecules, reduce the cost of drug research and development; In the clinical validation stage, intelligent analysis of clinical trial data by artificial intelligence is used to better understand the therapeutic effect of new drugs on different patients. In the future, we will see more cases of artificial intelligence applied to various links in the biomedical industry chain, and further enhance the industrial competitive advantage of biomedical related units through the application of artificial intelligence.

2. Field 2: Recombinant antibody technology

Recombinant antibody refers to antibodies produced using molecular biology techniques such as recombinant DNA. The most distinctive feature of recombinant antibodies is that the amino acid or DNA sequence encoding their antibody protein is known. Therefore, when preparing recombinant antibodies, people can insert the gene sequence encoding recombinant antibodies into the expression vector through recombinant DNA and other technologies, and transfer it to the expression host (such as mammalian cells, yeast or bacteria), and then express and purify to obtain a specific type of recombinant antibodies. Different from monoclonal antibodies produced by traditional polyclonal antibody/hybridoma technology, recombinant antibodies have the advantages of non-animal source production and high batch to batch consistency, which can meet the needs of large-scale antibody production, and control the quality stability of antibody production with a standardized production process.

Another significant advantage of recombinant antibodies is that they are easy to engineer. Recombinant antibodies can be humanized to reduce immunogenicity by means of molecular biology and synthetic biology. Or rearrange or replace the heavy chain, light chain or partial fragment region of the recombinant antibody to design the recombinant antibody with new antibody characteristics. Through phage display and other technologies, it is also possible to screen recombinant antibodies with high throughput for antibody performance, so as to quickly screen out those recombinant antibodies that can specifically target specific therapeutic significance. These properties allow recombinant antibodies to be modified into different forms for specific applications. For example, recombinant antibodies that specifically target histone post-translational modifications not only accelerate and improve epigenetic research, but also promise new research breakthroughs.

Recombinant antibody technology continues to develop, single-chain antibodies, nano-antibodies, bisspecific antibodies and other types of recombinant antibodies have also been widely studied in recent years, and many products have been approved for market. The booming development of technologies such as artificial intelligence has also made it possible to design more efficient recombinant antibodies more rationally and quickly. In addition, the preparation and production technology of recombinant antibodies are also continuing to expand, and the cell-free expression synthesis system is worthy of attention. Cell-free expression synthesis system is expected to produce a wider range of antibody products in a shorter time because it can further achieve host-free antibody production. Due to the flexibility of formulation regulation, cell-free synthesis technology can also be applied to the preparation and production of antibodies generated by AI designs that are difficult to express by the host.

At present, drug research and development based on recombinant antibodies has also become one of the mainstream of biopharmaceuticals. In the future, recombinant protein drugs will play a huge role in the prevention and treatment of diseases such as cancer, infectious diseases, immunity, endocrine metabolism and nervous system.

3. Field 3: Small molecule inhibitor technology

Small molecule drugs have been playing an important role in medical progress and addressing people's unmet needs, and it is also the largest drug type in the annual approval of new drugs (in 2022 FDA approved new drugs, small molecule drugs accounted for more than 50% [2]), the future, small subclass drugs are expected to continue to occupy a large proportion of new drug research and development. Small molecule inhibitor (Small molecule inhibitor) belongs to the small subclass of drugs, refers to a class of organic compound molecules with molecular weight less than 1000 Dalton that can target proteins, reduce protein activity or hinder biochemical reactions. Small molecule inhibitors reduce the activity of target proteins by directly binding to target proteins, competing with substrates, changing protein structure, or obstructing protein conformational transformation.

Small molecule inhibitors are commonly used in various drugs in clinical practice, including various proteins, enzymes, kinases, transcription factors, proton pumps, ion channel inhibitors, etc. Small molecule inhibitors are usually able to rapidly inactivate their targets and thus have significant advantages in finely regulating cell life and function, which makes them an important tool in life science research.

Due to the characteristics of small molecular weight, small molecule inhibitors have advantages compared with other types of drugs in terms of good oral absorption, easy penetration of cells, barrier transmission (such as blood-brain barrier), good pharmaceutical performance, and pharmacokinetic properties. These characteristics make small molecule inhibitors gain the favor of the market and new drug development. In recent years, thanks to the development of technologies such as artificial intelligence, computational chemistry, molecular docking, protein structure analysis and prediction, people can explore new targets of small molecule inhibitors more effectively, and carry out rational drug design of small molecule inhibitors, thus accelerating the research and development of new drugs of small molecule inhibitors. In the future, small molecule inhibitors will be more widely used in cancer treatment and other therapeutic areas, and more types of small molecule inhibitors will be available.

4. Field 4: High-throughput sequencing technology

High throughput sequencing refers to the sequencing of various biological sequences (such as DNA, RNA, protein, etc.) in a high throughput, fast, efficient, and economical manner. In the traditional sense, high-throughput sequencing usually refers to the specific high-throughput gene sequencing, the National Development and Reform Commission issued the "14th Five-Year Plan" bioeconomic development Plan proposed: "to speed up the development of high-throughput gene sequencing technology, promote the single-molecule sequencing as a symbol of the new generation of sequencing technology innovation, and constantly improve the efficiency of gene sequencing, reduce sequencing costs." However, with the emergence of technologies for high-throughput sequencing of non-nucleic acid sequences such as proteins in recent years, the meaning of high-throughput sequencing has also expanded.

High-throughput gene sequencing technology is the cornerstone of many studies (such as genomics), and its emergence has played a revolutionary role in the development of life science and medicine. For example, thanks to high-throughput gene sequencing, the Human Genome Project, known as one of the three major scientific projects of the 20th century, was completed in 2003. In recent years, the development of high-throughput gene sequencing technology has been relatively mature, and its sequencing objects and application scenarios have been very diversified, such as: whole genome de novo sequencing, whole genome resequencing, whole genome methylation sequencing, whole exome sequencing, whole transcriptome sequencing, RNA sequencing, etc. Many new high-throughput gene sequencing technologies have also emerged, and technologies such as long-read sequencing, single-molecule sequencing, single-cell sequencing, and spatial transcriptome sequencing have brought new possibilities for biomedical research.

With the completion of the sequencing of the human genome, the focus of life science research may be expanded from genomics to proteomics. In order to deeply understand all the components and sequence information of proteome and further understand the molecular mechanism of life activities and disease occurrence, the key is to have the support of appropriate high-throughput protein sequencing technology. At present, high-throughput protein sequencing technology is not as powerful as high-throughput gene sequencing technology. However, the emergence of new high-throughput protein sequencing technologies, such as non-mass spectrometry high-throughput protein sequencing, protein high-resolution mass spectrometry, and single molecule protein sequencing, has also made this technology increasingly mature, and brought new research and industrialization opportunities.

China has a good research and development foundation and a huge potential market demand in the field of high-throughput sequencing, which lays a solid foundation for our country to achieve curve overtaking in this field. In addition, a major feature of the development of high-throughput sequencing technology is that it simultaneously relies on the coordinated development of biomedical hardware technology and information software technology. In recent years, the progress of software algorithms such as artificial intelligence and bioinformatics has also brought new opportunities for the development of high-throughput sequencing technology. Through smarter information technology, people can analyze sequencing big data in a more efficient and automated way to obtain meaningful sequencing results. In the future, high-throughput sequencing technology will be more widely used in the field of biomedicine and become an important cornerstone of modern medicine such as precision medicine. High-throughput protein sequencing may become a new industrial growth point after high-throughput gene sequencing.

5. Field 5: Drug conjugate technology

Drug conjugate refers to a class of drugs that can be generated using specific linkers (usually chemical chains) to link ligands with effector molecules that have targeting properties. The key idea is that localization ligands can play the role of targeting delivery, and effector molecules can play the role of therapy. In general, the composition of drug couplings can be summarized by the formula of "localization ligand-link-effector molecule". According to the differences in the types of localization ligands, drug couplings can be further subdivided into: Antibody drug conjugate (Antibody-drug conjugate), Peptide drug conjugate (peptide-drug conjugate), Protein drug conjugate (protein-drug conjugate), Small-molecule drug conjugate (small-molecule) drug conjugate), Polymer-drug conjugate (polymer-drug conjugate), Radionuclide-drug conjugate (radionuclide-drug Conjugate), Virus-like drug conjugate (virus-like drug conjugate) conjugate), etc.

Take the representative antibody drug conjugate (ADC), which has been developed well in recent years, as an example. By using antibody as a localization ligand, the composition of ADC can be expressed as "antibody-link-effector molecule". Compared with traditional drugs, ADC has better targeting of drug delivery. In 2000, the first ADC was approved by the FDA for the treatment of acute myeloid leukemia, but it had drawbacks such as lethal toxicity. In recent years, ADC technology has been improving, and the incidence of adverse reactions of improved ADCs has also been significantly reduced. With new ADCs such as Brentuximab vedotin (trade name Adcetris) and Trastuzumab emtansine (trade name Kadcyla) approved by the FDA for the treatment of Hodgkin's lymphoma and HER2-positive breast cancer, ADC drugs have once again entered the field of research. At present, ADC still has a huge room for development. Advances in technologies such as directed coupling, polyvalent coupling, recombinant antibodies and small molecule drugs have brought new possibilities for the development of ADC drugs, and ADC drugs based on single-chain antibodies, nanoantibodies, bisecial antibodies and other types of antibodies have continued to emerge.

With the continuous development of drug conjugator technology, the types of localization ligands, effector molecules and linkers of drug conjugators will be increasingly diversified. In the future, we will see more types of drug couplings approved for clinical use, and the new generation of drug couplings will continue to bring benefits to patients.

6. Field 6: Therapeutic gene editing technology

Therapeutic gene editing refers to a class of therapies that achieve therapeutic effects through targeted editing of genes (knockout, insertion, replacement, modification, etc.).

One of the core technologies of therapeutic gene editing is the development of molecular tools that can efficiently edit genes. Gene-editing tools have been studied for decades. In 2020, the Nobel Prize in Chemistry was awarded to French scientist Emmanuelle Charpentier and American scientist Jennifer Doudna for "developing a method for gene editing," That is, CRISPR-Cas based gene editing, the breakthrough once again detonated a wave of gene-editing related research. CRISPR-Cas gene editing technology has the characteristics of wide editing range, easy to use, high efficiency and low cost, and is widely used in life science, drug research and development. In recent years, due to the increasing maturity of this technology, its direct clinical research in therapeutic gene editing has also increased. In March 2020, gene therapy based on CRISPR-Cas gene editing technology was used directly in humans for the first time to treat a patient with inherited blindness caused by Leber's congenital amaurosis.

In 2010, a CRISPR-CAS gene-editing therapy called exa-cel, developed by Vertex Pharmaceuticals and CRISPR Therapeutics to treat two inherited blood disorders, beta thalassemia and sickle cell disease, was granted fast-track approval by the FDA. The treatment is expected to be the first approved CRISPR-Cas gene editing therapy. In addition, many novel CRISPR-CAS systems have been developed and applied to emerging areas related to gene editing, such as RNA editing, single-base editing, lead editing, CRISPR interference (CRISPRi), and so on.

It should be pointed out that although there are a large number of studies on gene editing in the field of disease treatment, most of them are still in the pre-clinical laboratory research stage. How to further optimize the efficiency, accuracy and scope of editable gene sequences? And reduce the safety risks caused by off-target effects of gene editing or promote its wide application in the field of therapy and achieve the key to industrialization. In addition, CRISPR-Cas is not the only technological path to achieve therapeutic gene editing, and many other types of gene editing technologies are still worthy of continued attention, such as therapeutic gene editing technologies based on transposons, transcription-like activator effectants nucleases, zinc finger nucleases, etc. In the future, we will see the birth of more new technologies related to therapeutic gene editing, and humans will be able to cure some diseases (such as genetic defects) in an unprecedented way.

7. Field 7: Cell Therapy Technology

Cell therapy is a type of therapy in which living cells are transplanted into a patient to achieve a therapeutic effect. Cell therapy can be further subdivided according to the type of therapeutic cells used, such as cellular immunotherapy based on immune cells, stem cell-based stem cell therapy, etc.

Cellular immunotherapy works by implanting engineered immune cells into the body. In terms of cellular immunotherapy, Chimeric antigen receptor T cell (CAR-T) therapy has made rapid breakthroughs in recent years. The main principle is to introduce the engineered CAR (a synthetic transmembrane receptor) gene into T cells, and then cause T cells to specifically kill tumor cells expressing specific tumor antigens. In 2017, the first CAR-T therapy (developed by Kymriah) was approved by the FDA for the treatment of acute lymphoblastic leukemia. As of April 2022, five other CAR-T therapies have been successively approved by the FDA [3]. However, at present, CAR-T therapy has only achieved good clinical efficacy in hematoma, and the main challenge is how to enable engineered immune cells to be applied to the treatment of a wider range of cancer types, especially solid tumors. In view of this, people are also continuing to develop many new cellular immunotherapies, such as: CAR therapy based on non-T cells (such as CAR-NK immunotherapy based on NK immune cells, etc.), and cell immunotherapy based on non-CAR synthesis of transmembrane receptors (such as synthesis of Notch receptors, etc.).

Stem cell therapy uses the self-renewal ability and multi-differentiation potential of natural or induced stem cells to repair or rebuild the function of diseased/senescent cells/tissues, thus achieving therapeutic effects. In clinical practice, in addition to natural stem cells (such as cord blood stem cells, mesenchymal stem cells, etc.) can be directly used for stem cell therapy, induced pluripotent stem cells, cell reprogramming and other technologies are also worthy of attention. Through induced pluripotent stem cells, cell reprogramming and other technologies, people can reverse the differentiation of cells under specific conditions to a stem-like state (or directly transdifferentiation into the target cell type) for treatment. Due to the potential to reverse the fate of cells, such technologies may also bring hope to the anti-aging field, which has huge market prospects but no significant breakthrough.

In the future, more types of cells will be developed for cell therapy; Personalized, customized cell therapy from the patient is expected to provide new treatment options for more incurable diseases.

8. Field 8: New drug delivery technologies

Drug delivery system (Drug delivery system) refers to the technical system that comprehensively regulates the distribution of drugs in the biological body in space, time and dose, and minimizes the accumulation of targets by enhancing the delivery of therapeutic drugs to their target sites, thereby improving the health of patients. Compared with traditional drug delivery systems based on conventional oral tablets, capsules, intravenous injections, inhaled preparations and transdermal patches, New drug delivery system refers to the use of new drug delivery technologies with high technical barriers as a whole (such as drug delivery technologies based on liposomes, nanoparticles, microspheres, exosomes, engineered AAV carriers, 3D printed drug preparations, etc.) to deliver various drugs. The new drug delivery system can improve drug efficacy and reduce toxic side effects by adjusting drug delivery and release location, changing drug metabolism behavior, improving drug slow-release and controlled-release properties, and penetrating physiological barrier (such as blood-brain barrier) properties. In 2018, the FDA approved Onpattro, the first RNAi drug with lipid nanoparticles as a delivery vector. In 2021, Comirnaty, the first mRNA vaccine approved as a delivery vector with lipid nanoparticles, was marketed. Overall, the number of new drug delivery system products that have been developed and marketed to date is still small. In the future, in order to meet the drug delivery needs of various new drugs (such as gene drugs, mRNA drugs, peptide and protein drugs, cellular drugs, etc.), we also need more innovative new drug delivery systems.

9. Field 9: Immune checkpoint inhibitors

Immune checkpoint inhibitor (Immune checkpoint inhibitor) refers to a class of immunotherapy drugs targeting tumors. Its main mechanism is to restore the immune system's ability to kill tumor cells by blocking a class of proteins called immune checkpoints, so as to play a role in tumor treatment. In 2018, American scientist James Allison and Japanese scientist Tasuku Honjo were awarded the Nobel Prize in Physiology or Medicine for their work on immune checkpoint inhibitors.

At present, the immune checkpoint inhibitors on the market are mainly monoclonal anti-body drugs targeting immune checkpoint PD-1/PD-L1 or CTLA-4. In 2011, the FDA approved the first immune checkpoint inhibitor, Ipilimumab, which targets CTLA-4, for the treatment of melanoma. After that, immune checkpoint inhibitors targeting PD-1/PD-L1 were successively approved for melanoma, lung cancer, bowel cancer and other tumors. In addition, a variety of immune checkpoint inhibitors targeting LAG-3, TIM-3, TIGIT, VISTA and other immune checkpoint targets are currently under development. In addition, bispecic antibodies are also a research and development focus of immune checkpoint inhibitors, and there are several bispecic antibodies that can simultaneously target PD-1/PD-L1 and CTLA-4. In the future, with more in-depth research on the mechanism of tumor immune regulation, it is expected to develop more immune checkpoint inhibitors that can be applied to different tumor therapies.

10. Field 10: Brain-computer interface technology

In the questionnaire feedback of experts, brain-computer interface technology is relatively frequently mentioned and will have a potential significant impact on future biomedicine technology. A brain-computer Interface (BCI) is a human-computer connection that establishes a communication path between Brain signals and a machine (most commonly a Computer, chip, or robotic limb). Through brain-computer interface technology, people can extract and recognize memory, decision, emotion and other information encoded by the nervous system in the brain through the machine. Based on the brain information received by the machine, people can further regulate brain activity.

Bci has rich application prospects in brain science, neuropsychiatric disease research and clinical treatment, etc. For example, through BCI, people can better capture neural activity signals generated by different regions of the brain at different times and under different states, and then study the information encoding mechanism of the brain, which is also expected to inspire the development of new artificial intelligence algorithms. Through BCI, people can also better monitor the brain signals of different neuropsychiatric diseases under physiological and pathological conditions, crack the pathogenesis of diseases, and then develop targeted treatments for related diseases. People can also implant brain-computer interface chips that can stimulate nerves to correct faulty neural activity or promote the reconstruction of normal nerve signals, which is expected to treat some difficult brain-related diseases (such as epilepsy, vision loss, hearing loss, Alzheimer's disease, etc.); Bci is also used to restore the mobility of disabled or paralyzed patients, who can control an external limb through a non-invasive BCI to replace the function of a disabled limb.

According to the 14th Five-Year Plan for National Economic and Social Development of the People's Republic of China and the Outline of 2035 Vision Goals, brain science and artificial intelligence are national strategic scientific and technological forces, and brain-computer interface technology (brain-computer integration technology) is a key technology. In the future, brain-computer interface technology is expected to promote research breakthroughs in the field of brain science and artificial intelligence, and achieve broader applications in clinical fields such as diagnosis, treatment and rehabilitation of neuropsychiatric diseases.