The pharmaceutical industry is undergoing an unprecedented transformation thanks to the integration of artificial intelligence (AI), a process that has gained momentum since the COVID-19 pandemic. This advancement is not only redefining the way new drugs are researched and developed, but also optimizing the distribution of pharmaceutical products, marking a clear trend towards greater efficiency.
Innovation continues to be a focal point for the sector, and the use of digital technologies, including generative AI and digital twins, allows companies to achieve productivity levels never seen before. According to a recent study, the AI market is expected to reach $3.6 trillion by 2034, with the healthcare sector being one of the biggest beneficiaries of these technological advances.
One of the most significant contributions of AI is its ability to reduce both costs and time in the research and development phases. According to a McKinsey report, this technology can accelerate the design of complex molecules by more than three times, resulting in optimization in the selection of indications and the execution of clinical trials.
Projections for 2025 anticipate additional innovations that will include the use of generative AI in regulatory processes, facilitating more efficient analysis of regulations and speeding up the approval of new products. Additionally, data processing and text analysis will allow for extracting relevant information from large volumes of unstructured data, thereby improving decision-making.
Data centralization emerges as another key focus in this process, refining decision-making processes and streamlining operational protocols. Furthermore, the use of digital twins to simulate processes in real time helps minimize downtime and maximize productive capacity.
A vital aspect of technological advancement in pharmaceuticals includes implementing tools that allow for precise tracking of real-world results, improving the evaluation of drug safety and effectiveness. Additionally, AI plays a crucial role in optimizing pricing strategies, facilitating the identification of market trends and opportunities to enhance profitability.
Predictive models are gaining relevance in supply chain planning, an application where AI can have a decisive impact on process optimization and waste reduction. However, the adoption of these technologies faces significant challenges, such as protecting information security and the need to train personnel to effectively handle these tools.
In this context, Enterprise Resource Planning (ERP) systems have evolved to become an integral component in incorporating intelligent technologies. With the help of AI, ERP systems enable automated management of processes including inventory and distribution, significantly improving operational efficiency.
The new capabilities of ERP systems include anticipating demand and detecting anomalies in production, ensuring product quality. They also offer customization, adapting to the specific needs of each company within the pharmaceutical sector.
Quality management and documentation, essential elements in the pharmaceutical industry, benefit from platforms designed to ensure traceability and regulatory compliance. Quality Management Systems (QMS), when implemented alongside ERP systems, provide more comprehensive and optimized management, improving operational agility without sacrificing quality standards.
Thus, the pharmaceutical industry is on the brink of a future where artificial intelligence not only acts as an engine of innovation but also redefines the fundamental practices that govern the sector.
Referrer: MiMub in Spanish