First, 3D printing
3D printing can provide more opportunities for personalized treatment. The field of biological agents is exploring new ways to manufacture cell and tissue products through 3D printing.
For example, drugs and disease models can be tested on 3D printed tissues instead of animals or humans as before. When 3D printing is combined with nanotechnology, it can also be applied at the molecular level: customized white blood cells can be designed to hunt down and attack cancer cells.
Although the potential of emerging technologies such as 3D printing has been widely recognized, the supervision of these technologies is still in its infancy, even in more developed markets such as Australia.
Second, the blockchain.
Blockchain is composed of transaction blocks stored and linked on digital transactions. Transaction records can be shared and cannot be modified. It makes each patient's data source act as a complete and unchangeable "block" and then safely share it with health care providers or other research institutions.
The application of blockchain in the medical field has attracted more and more attention at home and abroad. The tentacles of blockchain have spread all over all walks of life, boosting the transformation and upgrading of traditional industries.
At present, blockchain technology has been gradually applied to the medical field. As a new technology, it is subverting the business model and even the value chain of this industry. A series of data show that the real potential of blockchain technology may lie in promoting cooperation by sharing digital assets between different companies and even industries.
Third, artificial intelligence (AI)
Artificial intelligence algorithms can analyze large data sets from clinical trials, health records, gene maps and preclinical studies. Patterns and trends in these data can verify clinical hypotheses faster than researchers and provide new insights quickly.
The latest application of artificial intelligence technology is in the field of diagnosis. In 20 17, Tencent launched the AI diagnostic medical imaging service called AIMIS.
At present, this technology has proved that the accuracy of initial diagnosis of esophageal cancer is over 90%, the accuracy of pulmonary sarcoidosis is 95%, and the accuracy of diabetic retinopathy is 97%. Up to now, AIMIS laboratory has been established in more than 10 hospitals, and further deployment agreements have been signed.
Youtu Lab, the artificial intelligence research laboratory of Tencent, also cooperated with the Esophageal Cancer Research Institute of Cancer Center of Sun Yat-sen University in Guangzhou to use thousands of anonymous patient data to train the diagnostic part of its AI technology. This development may have a significant impact on the process of drug development.
For example, the images captured by Tencent AI technology can be combined with xtalpi, which is a technology that uses cloud computing platforms (such as Amazon Web Services, Tencent Cloud, Google Cloud and Alibaba Cloud) to run algorithms and deploy/kloc-0.00 million computing power cores to discover new products in computers, greatly reducing the time and huge investment required for pharmaceutical companies to develop new products.
Fourth, gene therapy.
Gene therapy provides the possibility of personalized therapy, such as the new CAR-T therapy. Although the utilization rate is still low, human genetics and precision medicine have gradually changed medical care through innovative biotechnology.
Verb (abbreviation of verb) data helps the development of life, health and medical industry
Health data is the new currency of health care. Facing the continuous influx of more and more data from inside and outside, hospitals will rely on cognitive analysis to find and sort out the most important nodes and trends in the data, and make feasible suggestions to clinicians and patients through systematic and structured analysis of the data.
Three technologies are helping the Asia-Pacific region to tap different data sources, namely the Internet of Things, cognitive computing and cloud-based interoperable EHR systems:
1, Internet of Things
The development of the Internet of Things is of great value for remote clinical monitoring, chronic disease management, preventive nursing, assisted living and health monitoring of the elderly. The application of the Internet of Things also helps to reduce costs, improve efficiency, and shift the focus to quality patient care.
2. Cognitive computing
Cognitive computing includes machine learning, neural network and deep learning technology, which can help medical institutions to deal with a large number of rapidly changing data.
Cognitive computing can process various statistical algorithms and quickly generate new models of new data, which will help a large number of health care data (summarized from medical equipment, smart phones, activity tracking programs and EHR) to be transformed into personalized medical programs.
More importantly, cognitive computing can also be used to predict health trends (such as disease outbreaks), detect data patterns (such as the impact of drugs on individuals or groups), or enable data from different sources to be shared (such as creating a 360-degree view of patients).
3. Interactive operation of EHR system based on cloud.
When combined with artificial intelligence, interoperable EHR can help medical systems better integrate data into daily care and enable patients to better manage their own data. When these data are stored in the cloud, relevant personnel can access these data as needed, or they can access them on the blockchain, which is a distributed and unchangeable digital trading account book.
However, with the increase of data usage and the attack of ransomware such as Wannacry, network security and data risk management have become challenges for life sciences and health care industries.
In fact, in the annual cyber attacks, medical care is second only to the financial sector. Around the world, governments are studying new regulations to enable patients to control their own data and simplify the regulatory environment.
For example, the Japanese Ministry of Health, Labor and Welfare (the main department in charge of medical care and social security) released the latest version of the Health Information System Security Guide in May 20 17, aiming at promoting a series of measures to deal with the risk of cyber attacks in medical institutions.
Recently, Japanese medical institutions generally adopt closed systems to reduce network threats. However, the implementation of the new medical ID and data sharing scheme in Japan's national health system will require medical institutions to upload data to external servers, thus enhancing the importance of network security.