I. 3D printing
3D printing can provide more opportunities for personalized treatment. The field of biologics is exploring new ways to manufacture cell and tissue products with 3D printing.
For example, drugs and disease models can be tested on 3D-printed tissues, no longer on animals or humans, as was previously the case. When 3D printing is used in conjunction 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.
While the potential of emerging technologies such as 3D printing is widely recognized, regulations for these technologies are still in their infancy, even in more developed markets such as Australia.
Blockchain
Blockchain is built from blocks of transactions that are stored and linked to digital transactions, the records of which can be ****enjoyed and unmodifiable, enabling each patient's data source to act as a complete, immutable "block" that can then be securely shared with healthcare providers or other research organizations***. ***Sharing.
The application of blockchain in the medical field is gaining attention both at home and abroad, and blockchain's tentacles have spread to various industries, boosting the transformation and upgrading of traditional industries.
At present, blockchain technology has been gradually applied in the medical field, and as an emerging technology, it is subverting the business model and even the value chain of this industry. A series of data shows that the real potential of blockchain technology may lie in facilitating cooperation by allowing different companies and even industries to share digital assets with each other.
Three: Artificial Intelligence (AI)
Artificial intelligence algorithms can analyze big data sets from clinical trials, health records, genetic profiles and preclinical studies. Patterns and trends in these data can validate clinical hypotheses faster than researchers and quickly provide new insights.
One of the latest applications of AI technology is in the diagnostic space. in 2017, Tencent launched an AI diagnostic medical imaging service called Artificial Intelligence Innovative Medical System (AIMIS).
Currently, this technology has demonstrated an initial diagnostic accuracy rate of more than 90% for esophageal cancer, 95% for lung nodular disease, and 97% for diabetic retinopathy. To date, AIMIS labs have been established in more than 10 hospitals and agreements have been signed for further deployment.
Tencent's AI research lab, Youtu Lab, has also partnered with the Esophageal Cancer Institute at Sun Yat-sen University Cancer Center in Guangzhou to train the diagnostic portion of its AI technology using data from thousands of anonymous patients. Such developments could have a major impact on the drug development process.
For example, images captured by Tencent's AI technology can be used in conjunction with xtalpi, a technology that deploys a million cores of computing power using cloud computing platforms (such as Amazon Web Services, Tencent Cloud, Google Cloud, and AliCloud) to run algorithms to discover new products in computers, drastically cutting down the amount of time and the huge investments required by pharmaceutical companies to develop new products.
four, gene therapy
Gene therapy offers the possibility of personalized therapies, such as the new CAR-T therapies, and while usage is still low, human genetics and precision medicine are already progressively transforming healthcare through innovative biotechnology.
V. Data powering the life healthcare industry
Health data is the new healthcare currency, and in the face of a sustained, ever-growing influx of data from both internal and external sources, hospitals will rely on cognitive analytics to discover and sort through the most important nodes and trends in the data, and to provide actionable insights to clinicians, and patients, through systematic, structured analysis of the data.
Three technologies are helping APAC tap into different data sources, namely IoT, cognitive computing, and cloud-based interactive operational EHR systems:
1. IoT
The development of IoT is valuable for remote clinical monitoring, chronic disease management, preventive care, assisted living for the elderly, and health monitoring. The use of IoT also helps to reduce costs, improve efficiency, and shift the focus to quality patient care.
2. Cognitive Computing
Cognitive computing, which includes machine learning, neural networks, and deep learning technologies, can help healthcare organizations deal with large amounts of rapidly changing data.
Cognitive computing's ability to process a variety of statistical algorithms and quickly generate new models for new data will help transform large amounts of healthcare data (aggregated from sources such as medical devices, smartphones, activity-tracking programs, and EHRs) into personalized healthcare solutions.
More importantly, cognitive computing can also be used to predict health trends (e.g., disease flare-ups), detect patterns in data (e.g., the effect of a drug on an individual or a group), or enable the ****ing enjoyment of data from disparate sources (e.g., the creation of 360-degree patient views).
3. Cloud-Based Interactive EHR Systems
When combined with AI, interactive EHRs can help health systems better integrate data into daily care and enable patients to better manage their own data. When this data is stored in the cloud, it can be accessed by the appropriate people as needed, or on the blockchain, which is a distributed, unchanging ledger of digital transaction records.
However, with the increased use of data and ransomware attacks like Wannacry, the issues of cybersecurity and data risk management are becoming challenges that the life sciences and healthcare industries need to face.
In fact, healthcare is second only to the financial sector in terms of cyberattacks that occur each year. Globally, governments are working on new regulations that give patients control over their data and simplify the regulatory environment.
For example, Japan's Ministry of Health, Labor and Welfare (the main ministry responsible for healthcare and social security) released the latest version of its Health Information System Security Guidelines in May 2017, aiming to promote a range of measures to address the risk of cyberattacks in healthcare organizations.
Recently, it has become common for healthcare organizations in Japan to adopt closed systems to reduce cyber threats. However, the implementation of Japan's National Health System's new Medical ID and Data*** Sharing Program will raise the importance of cybersecurity by requiring healthcare organizations to upload data to external servers.