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in recent years, ai (artificial intelligence) technology has shown great potential in the medical and pharmaceutical fields. however, due to the serious nature of medical and pharmaceutical industries, ai technology has also encountered unprecedented challenges in the medical and pharmaceutical fields.

on the morning of september 6, the "2024 inclusion·the bund conference insights forum" hosted by the national business daily was officially held in the shanghai huangpu expo park with the theme of "ai pharmaceutical revolution: the road to industrial chain innovation". many important guests from academia and industry discussed in depth how ai can reshape the entire industry chain from drug research and development, production, circulation to application, focusing on the innovative application of ai technology in drug discovery, personalized medicine, precision treatment and other fields.

during the two and a half hour forum, voices from different technical fields, different industrial backgrounds, and different regions converged. and this is just the beginning. in china, a land of innovation that embraces all, the wave of ai and pharmaceutical integration has already surged, and will continue to lead the way of innovation in the industrial chain.

top experts in the industry discuss how ai can reshape the pharmaceutical industry chain

from drug discovery to precision medicine, ai is constantly breaking through traditional technology bottlenecks, accelerating the pace of innovation, and ushering in a new era for the pharmaceutical industry.

through advanced technologies such as deep learning and big data analysis, ai can assist doctors in diagnosing diseases, achieve early screening and prediction, and improve diagnostic accuracy. at the same time, it can also optimize treatment plans, achieve personalized medicine, and ensure that each patient can get the treatment strategy that best suits them. in addition, the application of ai in drug research and development has also accelerated the development of new drugs, reduced research and development costs, and provided strong technical support for overcoming difficult and complicated diseases. ai technology is gradually becoming a key force in promoting changes in the medical and pharmaceutical fields, contributing to the health and well-being of people around the world.

but at the same time, due to the serious nature of medical care and the high difficulty and high risk of new drug development, ai technology has also encountered unprecedented challenges in the medical and pharmaceutical fields.

in order to explore the difficulties in applying ai technology in the medical and pharmaceutical fields and improve the application level of ai technology in this field, on the morning of september 6, the "2024 inclusion·bund conference insights forum" hosted by the national business daily was officially held in the shanghai huangpu expo park.

the forum, with the theme of "ai medical revolution: the road to industrial chain innovation", brought together top experts, scholars and industry leaders in the industry, focusing on the innovative application of ai technology in drug discovery, personalized medicine, precision treatment and other fields, exploring how to improve drug development efficiency through intelligent means, meet patients' expectations for efficient and personalized treatment, and deeply discussing how ai can reshape the entire industry chain from drug development, production, circulation to application. it aims to promote the intelligent transformation of the biopharmaceutical industry through interdisciplinary exchanges and cooperation, and inject the warmth of science and technology into future health.

at the meeting, zhou hanmin, member of the standing committee of the national committee of the chinese people's political consultative conference and president of the shanghai public diplomacy association, delivered a keynote speech on the theme of "development and innovation of new medical industries in the era of artificial intelligence."

zhou hanmin photo source: provided by the organizer

zhou hanmin said that with the continuous development and application of new technologies such as artificial intelligence, the medical industry is ushering in a profound change. taking the construction of new quality productivity as a starting point and better combining it with artificial intelligence is the top priority for the future development of the medical and health industry.

according to his observation, from the initial imaging diagnosis, auxiliary diagnosis and treatment, genetic testing to drug discovery, clinical trials, health management, etc. in recent years, artificial intelligence has significant advantages in improving accuracy and efficiency, personalized treatment, and data processing.

the new round of scientific and technological revolution and industrial transformation is advancing by leaps and bounds. new technologies must be used to cultivate new models, new formats, and new momentum to lead industrial transformation and upgrading. zhou hanmin believes that building new quality productivity in the medical industry can be mainly approached from three dimensions: first, promoting the close integration of artificial intelligence and clinical practice to improve accuracy. second, optimizing data sets and model architecture to improve applicability. third, strengthening data privacy protection and improving security.

regarding the outside world's discussion on whether the development of artificial intelligence will replace medical staff, zhou hanmin said that artificial intelligence is an important assistant to medical staff, but medical staff will never be replaced. "artificial intelligence cannot replicate the emotional virtues of doctors, such as empathy, compassion and humanistic care. medical staff should correctly view and actively embrace artificial intelligence."

ai technology helps early identification and prediction of alzheimer's disease

in the field of drug research and development, cheng wei, a researcher at the institute of brain-inspired intelligence science and technology of fudan university, delivered a keynote speech on how ai technology can assist in the development of alzheimer's disease (ad) drugs.

every 3 seconds, there is one more dementia patient in the world, of which about 60% to 80% will be diagnosed with alzheimer's disease. early intervention of alzheimer's disease is the key to treatment, but in china, the rate of early clinical consultation for ad patients is only 14%. cheng wei said that this is because ad has an insidious onset, the evolution of biological indicators at each stage is not clear, and the accuracy and interpretability of early risk identification models are insufficient, making early identification and prediction of ad very difficult, which also greatly affects the efficacy of ad treatment drugs such as monoclonal antibodies.

therefore, obtaining non-clinical data of ad patients and building early risk identification models are the key to ai-assisted early prevention and treatment of ad, among which big data and algorithms are two important pieces of the puzzle.

in july this year, a team led by professor yu jintai from the department of neurology at huashan hospital affiliated to fudan university, in collaboration with the teams of feng jianfeng/cheng wei from the institute of brain-inspired intelligence science and technology of fudan university, published a paper in nature human behavior, unveiling a new biomarker, ywhag.

image source: provided by the organizer

in his keynote speech, cheng wei gave a detailed introduction to the relevant research. he said that the discovery and early identification of new markers cannot be separated from the assistance of big data and ai algorithms.

cheng wei introduced that the science and technology innovation 2030 - "brain science and brain-like research" major project, led by professor yu jintai of the department of neurology of huashan hospital affiliated to fudan university, has established a community brain health aging cohort (head cohort) across the country based on huashan hospital. it aims to recruit 20,000 participants from different regions of china, conduct longitudinal studies through long-term follow-up, and depict the whole process of an individual's gradual development from a healthy state to dementia symptoms.

"with big data and ai algorithms, what we do is to use them to discover new markers for ad diagnosis." cheng wei said that it takes about 20 years for ad to develop from the asymptomatic stage to the symptomatic stage, and cerebrospinal fluid biomarkers are the first to change in the course of ad. therefore, the team's first research work is to focus on the cerebrospinal fluid proteome data of a large population, and based on these data, develop a generative analysis algorithm to identify proteins related to ad.

during this process, the team screened out several biomarkers significantly associated with ad from thousands of cerebrospinal fluid proteins. based on a series of studies, the research team built a prediction model based on machine learning, sorted the importance of proteins by the effect value method, and the results were highly consistent with clinical findings. in the end, the prediction model built by the team was able to predict the risk of ad 15 years in advance, providing potential for community screening.

"in addition to ad, we also hope to extend the model to risk warnings for other elderly diseases." cheng wei revealed that the team has also built a multi-disease early prediction model based on blood proteomics and a protein risk prediction model based on neural networks. he believes that in the future, through digital platforms and large model frameworks, early warnings and interventions for more community populations and more diseases can be achieved.

the industry calls for the use of ai to improve the scientific nature of new drug development decisions

during the keynote speech session, yu rong, chairman of meinian health, also shared the innovative applications of ai technology in the field of physical examinations with the theme of "ai empowers healthcare: catalyzing new quality productivity of health examinations".

yu rong mentioned in his speech that after the epidemic, in addition to investing the main resources and energy of meinian health in basic operations, refined improvements, and discipline construction, it also spent a lot of energy and invested a lot of resources in artificial intelligence and data mining.

in the past five years, the ai-driven medical technology cloud platform developed by meinian health, including the saas bian que management system, has built a network of ai infrastructure. for example, the bian que physical examination management saas cloud platform can realize the digital and intelligent management of the entire physical examination process; through the pacs system (image archiving and communication system), it can realize the online storage, archiving and communication of pacs images, and improve the level of artificial intelligence in image reading; through the lis system (hospital laboratory information system), it can realize the intelligent upgrade of information management in the laboratory department.

yu rong said that in the future, he hopes that based on meinian’s data entrance and traffic entrance, he can incubate a better ecosystem and form a synergistic effect in some key areas, including chronic disease management in key disciplines, health consumption, health products, insurance, and advanced equipment.

zhou hanmin photo source: provided by the organizer

wang xingli, executive president of fosun pharma, co-ceo of the innovative drug division, and ceo of the global r&d center, shared the r&d ecosystem capabilities of ai+pharmaceuticals. in his speech, he said that in the field of drug r&d, quantitative decision-making and the success rate of new drug r&d are still the two major challenges that ai technology needs to overcome.

taking the quantitative decision-making process as an example, wang xingli believes that by using ai tools to provide a quantitative conclusion in global information, "it can help companies decide whether to build this pipeline or develop this product, which can improve the success rate of decision-making."

in terms of the success rate of new drug development, he said that the failure rate of each node of new drug development is very high. why is it unsuccessful? the simplest reason is that the drug is not right and the mechanism is not right. "but sometimes it may be a good drug, but the patient is wrong; sometimes the patient is right, but the endpoint is wrong; sometimes the time of taking the drug is wrong or the time of treatment is wrong. there are actually many differences in various human judgments."

"if you choose the wrong track, patient, target, and end point, no matter how effective it is, the higher the efficiency, the greater the waste. therefore, we should use the power of ai more to improve the success rate of new drug research and development," wang xingli concluded.

at the roundtable session, ren feng, co-ceo and chief scientist of insilicon valley, wang xiao, vice president of iflytek medical, mao hua, partner and managing director of frost & sullivan greater china, and zhang yaru, attending physician of huashan hospital affiliated to fudan university, discussed "the opportunities and challenges that ai brings to clinicians" and conducted in-depth discussions on the application of ai in new drug development and precision medicine.

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