Introduction | In recent years, with the development and application of AI and other technologies, digitalization and intelligence have gradually become emerging forces for the transformation and upgrading of all walks of life, and their integration and innovation with the pharmaceutical industry has gradually become the current new trend. Many pharmaceutical manufacturing companies are gaining momentum Ready to go, take the express train of digitalization and drive into the fast lane of high-speed development. Today, we invited Mr. Han Guangzu, Tencent Cloud TVP Industry Ambassador, Sunyuan Technology Partner & CTO, to share with us his unique insights on digital development and innovative applications of pharmaceutical companies.
About the Author
Han Guangzu, Tencent TVP Industry Ambassador, Sunyuan Technology Partner & CTO, Master of Business Administration, University of Southern California, has more than 26 years of experience in enterprise IT/MIS/IS digital transformation, innovation, and operation, including software and hardware engineering, including professional Experience in service solutions, planning, implementation, establishment of large-scale data analysis, deep learning of data collection and image object detection, process optimization and telecom public cloud construction and development, familiar with business system analysis and overall strategic planning; more than 20 years Experienced in engineering team management, currently serving as CTO and partner of a technology company, has served as CIO/COO/of Wistron Group and Fubon Financial Holdings, two of the world's top 500 groups, and a veteran e-commerce ( http://Newegg.com ) VP/Director, has experience in manufacturing, software companies, bank Party A and Party B innovation, digital transformation, investment, pre-sales, M&A, and DD.
introduction
生物制药的数智化转型指的是应用现代数字技术，包括人工智能、大数据、云计算、物联网等，来优化生产、研发和供应链等环节，降本增效提质，从而加速创新，实现智能制造和智慧医疗的目标。在我看来，数智化转型的战略规划应该涵盖总体战略概述､ 战略框架､ 战略定位､ 战略目标､ 战略举措､ 总体架构概述､ 业务架构､ 业务架构､ 应用架构､信息架构､数字基础设施架构､ 企业开放平台架构-生态、场景、渠道、政府、金融。数智化转型是 BTE（业务、技术、人才）三位一体的全方位转型，涉及用户体验、业务场景、数据融合、数字平台、组织管理、制度规范、建设运营、信息安全、文化素养、敏捷驱动等关键要素，根据顶层设计需求，我们可以总结为“三阶十步”的设计方法。
（图1，三阶十步图）
（示例：参考2021生物医药数字化转型白皮书）
生物制药数字化转型势在必行
数字化转型已成为各行各业的共识，对药企来说，同样也不例外。药企可以通过使用数字化的产品与服务构建医药生态圈，提高研发、生产、营销等环节效率，实现各个环节的数据分析、高效协同、智能响应，重塑核心竞争力。在我看来，数字化转型将为生物制药带来以下四大方面的影响：
首先，生产自动化和智能化。通过物联网和大数据技术，实现生产设备的远程监控和智能控制，提高生产效率和质量稳定性，并减少人为误操作的可能性。
其次，数据驱动的研发。通过人工智能、机器学习和数据挖掘等技术，对生物制药研发数据进行深度分析和挖掘，加速新药研发和优化现有药物的疗效和安全性。
再者，智能供应链管理。通过区块链技术，建立全球化的供应链网络，实现药品质量追溯和全程可视化，加强对供应链的管控，提高供应链的透明度和稳定性。
最后，药物个性化治疗。通过基因测序等技术，获取患者的基因信息，针对不同基因型的患者，开发相应的个性化药物，提高治疗效果和安全性。
Overall, the digital transformation of biopharmaceuticals will accelerate changes and innovations in the industry, improve product quality and safety, reduce costs, and provide patients with better treatment options and services. In addition, the digital transformation of biopharmaceuticals will also promote the sustainable development of the biopharmaceutical industry, specifically in the following aspects:
- Saving energy and resources: Through the application of digital technology, energy saving, emission reduction and resource recovery in the production process can be realized, production costs can be reduced, and it is also conducive to environmental protection;
- Promote collaborative innovation: With the support of digital technology, interdisciplinary and inter-institutional collaborative innovation can be achieved, promoting technical exchanges and cooperation in the biopharmaceutical industry, and accelerating innovation and progress;
- Improve drug approval efficiency: Through the application of digital technology, the drug approval process can be optimized and accelerated, the approval cycle can be shortened, and patients can be provided with faster new drug launch services;
- Strengthen drug supervision: With the support of digital technology, it is possible to realize the intelligence and refinement of drug supervision, improve the efficiency and quality of supervision, and ensure the safety of patients' medication.
To sum up, the digital transformation of biopharmaceuticals is an inevitable trend with great significance and value. With the continuous development and application of digital technology, the biopharmaceutical industry will usher in a broader development space and more opportunities.
Difficulties in digital transformation of biopharmaceuticals
As a highly regulated industry with extremely high safety requirements, biopharmaceuticals have the following pain points in equipment and control processes:
(Figure 2, pharmaceutical equipment flow chart)
- High equipment cost: The pharmaceutical industry needs to use high-precision and high-standard equipment to ensure the quality and safety of products, which leads to a substantial increase in equipment costs and requires pharmaceutical companies to invest a lot of money in equipment;
- Long R&D cycle: The pharmaceutical industry needs to carry out a lot of research and development work to ensure the safety and effectiveness of products, which requires a lot of time and resources, increasing the development costs of pharmaceutical companies;
- High reliance on manual operations: Although the pharmaceutical industry has begun to adopt automation technology, in some production stages, a large number of manual operations are still required to ensure the quality and safety of products, which increases the production costs of pharmaceutical companies;
- Highly regulated quality control, complex processes and compliance: The pharmaceutical industry needs to ensure product quality and compliance with regulations, which requires strict quality control and supervision, including the entire production process from raw material procurement to finished product quality testing monitoring;
- New technologies and innovations: With the emergence of new technologies, the pharmaceutical industry also needs continuous technological innovations to improve product safety and efficacy, and improve production processes and process controls. This requires pharmaceutical companies to continuously invest funds and human resources in research and development and testing, which increases the company's research and development costs;
- Internationalization and competition: With the internationalization and globalization of the pharmaceutical market, pharmaceutical companies need to face fierce competition from all over the world, which requires pharmaceutical companies to maintain competitive advantages in product quality, innovation, cost and marketing. At the same time, pharmaceutical companies also need to consider the regulations and standards of different countries and regions to ensure that products meet local requirements.
It can be seen that pharmaceutical companies can use various methods to reduce costs in terms of equipment, raw materials and control processes, thereby improving their profitability and competitiveness. At the same time, in this process, enterprises should also ensure product quality and safety.
How AI technology is applied in biopharmaceuticals
Deep learning has a wide range of applications in industrial pharmaceutical equipment and control process solutions, which can help pharmaceutical companies improve production efficiency and quality, accelerate the drug development process, and achieve more personalized and intelligent production and services.
(Figure 3, AI fusion pharmaceutical equipment)
(1) Application of deep learning in pharmaceutical equipment
The following deep learning models can be applied to the data analysis and control of pharmaceutical equipment, as shown in the figure below. For example, reinforcement learning can be used to optimize equipment control strategies, and multi-task learning can be used to solve joint training for multiple tasks.
(Figure 4, deep learning model and its application)
In the pharmaceutical equipment and control process, we also face a series of problems such as the control and cleaning of the pure water system, the control of the sterilization equipment, etc., but with the help of AI technology, we can manage and record various data in the production process, Realize online monitoring and guarantee information and network security.
(Figure 5, pharmaceutical equipment and control pain points)
(2) Implementation of biopharmaceutical technology
The pharmaceutical process optimization cycle steps include the following aspects:
- Raw material optimization: By selecting high-quality raw materials and optimizing formulas, the quality and stability of products can be improved and production costs can be reduced;
- Process parameter optimization: Improve reaction efficiency, yield and product quality by optimizing process parameters such as reaction temperature, reaction time, solvent usage, and stirring speed;
- Equipment optimization: through the introduction of advanced equipment and technology to improve production efficiency, reduce costs and reduce pollutant emissions;
- Process optimization: reduce costs, shorten production cycles, improve product quality and reduce pollution by redesigning and optimizing pharmaceutical processes;
- Quality control optimization: by introducing modern quality control techniques and methods to ensure product stability, safety and effectiveness;
- Personnel training and management: By strengthening employee training and management, we can improve employee skills, work efficiency and safety awareness, and promote the sustainable development of the enterprise.
Undoubtedly, the birth of the granulator is a major breakthrough for the pharmaceutical industry. It is a pharmaceutical machine equipment used to compress powder or granular materials into solid particles. The process combines mixing and granulation Together, it saves time and meets GMP requirements, reduces cross-contamination, and improves granulation efficiency. It is a more popular equipment in the pharmaceutical market.
But when we use the granulator, we need to pay attention to these invisible variable factors such as the nature of the material, the parameter setting of the granulator, and whether the mold is worn and deformed. Since there are many invisible variables in the use of granulators, we need to pay attention to the influence of various factors in order to obtain the best granulation effect and quality in practice.
For example, the number of start-ups of a granulator in a pharmaceutical factory is calculated from historical data using a self-built function based on cleaning and operation rules. It is about 270 times throughout the year (generally 2 batches per day), and the main control waveform is stable and reaches the average value. A state of highs and lows.
As the time for normal production of a single batch, from historical data, it generally reaches a stable production process state after 35-50 minutes. If the steady state can be reached in 25 minutes, that is, the startup time of each batch is saved by 25 minutes, 25/150 = 0.17, and the production efficiency is increased by 17%. An investment of 1 million ROI will pay back in about 0.29 years.
(Figure 6, device application)
(3) AI intelligent control to create an energy-saving and low-carbon digital workshop
The digital workshop realizes scientific decision-making and real-time update of the algorithm through the Internet of Things, cloud computing, edge computing technology, and AI artificial intelligence algorithm. The original "multi-parameter + multi-constraint control algorithm" captures changes in working conditions at multiple points, and finally realizes independent parameter tuning. , continuously optimize energy efficiency.
(Figure 7, digital workshop diagram)
In the production workshop, it can be divided into public and auxiliary workshops (introduction to production workshops) and direct production workshops, which are also composed of air compression system, central air conditioning system and circulating water system. AI technology can realize intelligent control of each part, effectively achieve energy saving and emission reduction, and improve production efficiency. For example, the central air-conditioning system can achieve efficient operation of the main engine through intelligent optimization, saving energy consumption by 10-20%, while the circulating water system will perform intelligent dosing and intelligent adjustment through data models and analysis according to changes in water quality data.
(Figure 8, workshop introduction)
In the digitalized workshop controlled by AI, each station in the public auxiliary workshop can achieve an average energy saving rate of more than 10% through digital intelligence technology, and the energy saving principle of digital intelligence technology is mainly through the collection of factory production "energy demand side" and intelligent energy consumption. Controlling "equipment parameters on the energy supply side" to realize the supply and demand curve, this kind of energy saving and consumption reduction also coincides with the carbon neutral strategy advocated by the country. It is currently the most advanced intelligent control and energy-saving solution for public and auxiliary workshops. It mainly reduces operation and maintenance costs through data monitoring and visualization, and helps workshops save energy by 10-30% with the help of AI intelligent control.
(Figure 9, energy saving rate of public and auxiliary workshops)
(4) Grasp the hot spots of digital and intelligent transformation of pharmaceutical companies
In fact, the digital transformation capabilities of pharmaceutical companies are not only reflected in the ability to apply technologies such as artificial intelligence, blockchain, cloud computing, and big data, but also in the capabilities of digital management, operations, marketing, and innovation. Therefore, we should grasp some hot spots in the digital and intelligent transformation of pharmaceutical companies:
- Artificial intelligence and big data analysis change energy consumption, optimize processes and increase production capacity;
- Plan ahead for carbon assets and liabilities;
- Combination of scenarios, ecology, open platform and supply chain;
- The integration of information technology and business includes research and development, clinical practice, production, operation and maintenance, and patient services;
- Reengineering of the operating system; digital global marketing capabilities;
- Continuous open innovation: such as continuous innovation through innovation groups, joint laboratory projects, or the establishment of cross-departmental agile project teams, as shown in the figure below.
(Figure 10, the comparison between open innovation and closed innovation)
In the initial stage of the development of innovative projects, guidance and control are achieved through capital means, which complements the shortcomings of the traditional business of pharmaceutical companies in terms of Internetization. When the incubated projects meet their own needs, new businesses can be absorbed by means of capital increase and holding, such as trusts and SPVs. Into the enterprise itself, do a good job of value management through capital planning as a means of continuous operation or M&A mergers and acquisitions or sales of the company platform as a means of direct profit.
(Figure 11, Value Creation in Digital Transformation and Innovation)
At present, the digitalization of the biopharmaceutical industry has become the general trend. It is expected that with the development of technologies such as AI and the Internet of Things, pharmaceutical companies will usher in broader opportunities for transformation in the future.