Shortages of vital and non-essential drugs have been persistent over the last 15 years — from cancer treatments to hospital emergency and surgery essentials — burdening health care systems and compromising the care of patients. The issue became uncomfortably real recently, when patients had to go searching for a pharmacy that could fill a simple amoxicillin prescription.
Even as organizations continue their analysis and global agencies provide new guidance, the gaps in supply persist. This is especially true for generic medicines, which account for a majority of the prescriptions in Europe and the U.S. For some generics manufacturers, margins in the low single digits can make consistent quality and compliance feel out of reach. The costs of addressing a single warning letter can drive a small supplier out of business, further shrinking supplies.
But in a concerted effort that includes regulators, governments, patient advocates and industry groups, the industry is taking action to address today’s supply problems. By connecting quality, regulatory and manufacturing data, companies can bring agility across the supply chain.
A need for micro and macro data transparency
Regulators and suppliers are grappling with a lack of data transparency across the supply chain, preventing visibility into fluctuations in supply and their causes. Challenges with access to quality data for APIs and finished drugs manufactured offshore are increasing supply risks. Between 2020 and 2022, the FDA’s five-year inspection backlogs of offshore API facilities have increased from 30% to 80%. The agency is starting to pivot its approach, adopting remote and other inspection formats.
Other efforts are being made internationally as well. For example, the European Medicine Agency (EMA) has taken a critical first step by listing the generics most vulnerable to shortages. The effort should help guide plans and decision-making. To take this a step further, discussions have emphasized the need for economic incentives to help generics manufacturers advance how they work and improve data collection, monitoring, and analytics across the supply chain.
At the 'micro' individual facility and company level, organizations are prioritizing establishing a technology foundation that increases data transparency and connects it across functional areas. By enabling data-driven processes and decision-making, companies are increasing the efficiency of compliance and quality operations while reducing the risk of shortages.
Agile change control is possible with connected data
Post-approval change control is a time- and resource-intensive behind-the-scenes process that can often lead to delays. For companies with siloed data sources, disconnected IT systems, and manual processes, completing one change control process can take six months to two years. Considering the regulatory agencies and regional requirements involved, this work to report changes can delay a drug’s availability by up to five years.
The industry has a significant opportunity to improve change control and mitigate shortage risk. The typical large biopharma can manage up to 40,000 of these applications yearly and nearly 200 for a single product.
If the FDA approved a manufacturer’s new therapy two years ago and improvements have been made since then, companies need to attain separate regulatory approvals for each change. For example, if they’ve developed safer manufacturing processes that reduce product costs, want to use more sustainable packaging, or move from laboratory-based quality control to real-time batch release. Each of these individual improvements would require agency review and approval.
Getting all the necessary data together for each proposed change could take months. Regulatory teams must first determine the impact of each proposed change and then dig deeper into what countries and internal documents will be affected. The next step is having supply chain teams do the same for each product lot.
The quality team must then analyze and pull the changes to the broader organization. This includes identifying and updating existing documents and developing new training programs that reflect the changes.
Most regulatory and quality teams today use multiple software systems for each step, sharing information and communicating via email and phone. This increases the risk of noncompliance or, even worse, receiving a warning letter since the disconnected and manual nature of the workflow can lead to errors.
Even after compiling, publishing, and submitting the applications for change approval, regulatory teams must optimize engagement with regulatory agencies. Ultimately, regulators can still decide a reinspection of the facility is needed to re-approve the improved product, triggering additional delays in product availability.
Increase speed and lower costs with connected processes
Consider adopting a unified approach to managing quality and regulatory data to simplify and streamline change control. Suppose companies can shift from using multiple siloed systems toward connected applications on a single platform. In that case, users gain visibility across functional areas, which makes it easier to spot and address problems faster.
Bringing together regulatory, quality, and supply chain data, documents and processes can drive even greater agility. Connecting a corporate enterprise resource planning (ERP) system with regulatory and quality data and content is now possible, particularly critical product documentation.
Companies across therapeutic areas and all sizes are unifying their quality and regulatory data management to facilitate cross-functional collaboration. Taking this a step further, some are connecting this data with ERP systems, an advancement that can potentially lower batch release timelines by nearly 30%. With these changes, teams across functions gain the transparency to make compliance easier. This ensures accuracy and speed when completing change control processes, improvements that can help mitigate the risk of drug supply gaps.
The rising costs of disconnected systems in the supply chain
Every day that a drug isn't available to patients costs a manufacturer hundreds of thousands to millions of dollars, regardless of whether it's a specialized treatment or everyday over-the-counter medicine. Companies unifying quality and regulatory information are improving transparency, centralizing access to real-time data, and automating workflows. The changes have already proved they can accelerate access to critical treatments patients need.
Assessing the time and cost of using traditional approaches to manage change control can reveal surprising learnings into the total cost of ownership of maintaining legacy approaches. Consider the opportunity to drive savings and improvements in the following areas:
- Freeing valuable time for highly trained and qualified people, moving away from manual and administrative tasks toward priority activities, like engaging with regulators
- Lowering the need for one-off email and mobile communications, measured by the hours each staff member spends on these efforts every day, within teams and across functions
- Strengthening patient and healthcare providers’ trust in access to critical treatments. Although this can’t be measured, quantifying missed product release deadlines over time could offer insight into performance gaps and trends
- Mitigating the intangible, but often significant, brand reputation costs of having a drug shortage
The challenges of not having access to real-time data across systems can affect name-brand, generic, and medical device manufacturers alike. Changing control is only one of multiple behind-the-scenes operations that can drain time and resources and delay the delivery of treatments to patients.
As we continue to manage existing drug supply shortages, the experience reminds us that we are all patients, and life sciences supply chain issues affect us all. Solutions exist today to help drive automation for behind-the-scenes processes and maximize access to connected, real-time data. The approach can only work if individual plants and their supply chain partners adopt a foundation for data transparency, one step at a time.
