November 20 2023 0Comment

AI in Pharmaceutical Production: Is India Ready For That?

Artificial intelligence is successfully crossing one level after another in its test of utility, especially in science and innovation. AI is speeding up the process by collecting and accessing the information, drastically minimising the time in drug discovery. It also plays an essential role in checking the prices of new treatments.

Developing a new drug costs around $985 million in the US and India; it ranges between 10-15 million rupees. This includes a high level of technical expertise and human resources. The cost of drug development 

The Indian pharmaceutical industry is a leading force globally in manufacturing and supplying quality-assured medicines to more than 150 countries. 

Hollywood has long portrayed artificial intelligence (AI) as a far-fetched notion, but technology has already bridged the gap between science fiction and science fact. AI is here to stay, with half of global healthcare organisations planning to apply AI strategies by 2025. 

How is AI going to bring a change in the pharmaceutical industry?

AI has the potential to revolutionise process design and control for pharmaceutical producers, bringing benefits to patients but posing hurdles to regulators.

Because of its fictionalised history, the term AI can imply various things to various people. 

The FDA’s Centre for Drug Evaluation and Research (CDER) defines AI most efficiently. It explains AI as “a branch of computer science, statistics, and engineering that employs algorithms or models that exhibit behaviours such as learning, decision-making, and prediction.” 

AI can aid pharmaceutical producers by optimising process design, control, and smart monitoring and maintenance. AI- usage shall promote continuous improvement. Combined with other novel technologies. AI can improve pharmaceutical quality, establish robust supply chains, and increase patient access to medicine. The pharmaceutical industry is proactively preparing for the best utilisation of AI technology in pharmaceutical manufacturing in anticipation of these benefits.

How might drug manufacturers use artificial intelligence in process and control? 

  • Optimisation of the process and scaling up: Machine learning AI models may leverage process development data to build and identify ideal process parameters or scale-up methods more quickly, minimising development time and waste.
  • Process management: Advanced process control may provide dynamic control of a manufacturing process, which, when combined with real-time sensor data, may be utilised to construct process controls that can precisely forecast a process’s trajectory. Pharmaceutical companies plan to use enhanced process control approaches that combine AI technology with chemistry and physics understanding to increase manufacturing efficiency and output.
  • Monitoring the process and detecting faults: AI approaches could improve equipment monitoring and detect deviations from optimal performance. AI-detected deviations may initiate maintenance tasks in a way that reduces process downtime.
  • Trend analysis: AI methods combined with process performance metrics may provide better trend monitoring, even across products or locations, allowing for proactive corrective and preventive actions to address manufacturing discrepancies before they impact the supply chain or, in the worst-case scenario, cause drug shortages.

The potential use of AI to monitor quality continues beyond there. AI could also be used to monitor a product’s quality after it has been manufactured, such as the integrity of its packaging or the presence of particles. A vision-based quality control system may utilise AI to analyse photos of packaging, labels, or glass vials to detect deviations. Aside from the product, The Pharmaceutical industry might use AI to develop high-quality pharmaceuticals that should be offered to patients constantly.

How the use of AI in the pharmaceutical industry is regulated?

Even from the viewpoint of economic improvement, the involvement of AI can’t be avoided, as keeping in consideration of the inherent strength in manufacturing, digital talent and favourable demographics, India has the potential to become a life-sciences innovation hub and grow its market to $120-130 billion by 2030 and $400-450 billion by 2047.

With the increasing potential of the pharmaceutical industry in the country, it became necessary to implement a robust framework of law to regulate and manage the whole procedure without compromising the country’s progress.

The Indian Government, following the incidents of several countries reporting deaths allegedly linked to the drugs manufactured in India, the Government is desperate to implement revised Good Manufacturing Practices. (GMP) to get it at par with the standard set by the World Health Organization.

Larger corporations with over Rs 250 crore turnover are instructed to implement the modifications by the first quarter of 2024. Meanwhile, medium and small-scale organisations with a turnover of less than Rs 250 crore must do so by the third quarter.

This comes as India promotes itself as a global manufacturing hub for generic drugs.

Why the revision in GMP is becoming an urgent matter?

There are specific reasons why the Indian government gives the revision in GMP such a high importance; they are as follows:

First, the new regulations will bring the Indian industry up to global standards.

Second, some countries have reported alleged contamination in India-made syrups, eye drops, and eye ointments in several incidents. These goods have been linked to the deaths of 70 children in the Gambia, 18 children in Uzbekistan, three people in the United States, and six people in Cameroon. This revision will check the drug manufacturing process of the large, medium and small manufacturers. Moreover, we can not ignore that only 2000 out of 10,500 drug manufacturing units in the country are at par with global standards set by WHO.

Third, the government discovered several flaws during a risk-based inspection of 162 manufacturing units. They included –

  • incoming raw materials not tested before use,
  • product quality not reviewed,
  • a lack of quality failure investigation,
  • a lack of infrastructure to prevent cross-contamination,
  • faulty design of manufacturing and testing areas,
  • a lack of qualified professionals, and
  • poor documentation.

The higher criteria would ensure that pharmaceutical businesses adhere to established processes and quality control systems and do not cut corners, increasing the quality of medications offered in India and worldwide.

In reality, one of the solutions proposed during a Chitan Shivir following the string of occurrences was the implementation of revised good manufacturing practices (GMP) as listed in the 2018 draft Schedule M of the medicines and cosmetics rules. The stakeholders also proposed developing a national IT platform to promote uniformity across states in licencing and inspection processes, among other things, guaranteeing that the quality of medicine manufactured anywhere in the country is the same.

What Shall be the benefits of the new revised GMP?

When discussing AI’s involvement in pharmaceutical production, the new GMP guidelines emphasise quality control procedures, accurate documentation, and IT support to ensure the quality of manufactured medications.

As per a news report, the new guideline describes the pharmaceutical quality system, quality risk management, product quality evaluation, and equipment validation. Companies will have to do frequent quality reviews of all their products, ensure the consistency of the quality and procedures, conduct a full investigation of any deviation or suspected fault, and execute appropriate preventive actions. It also recommends a change control system to analyse all changes that may affect product production or quality.



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