Building connected care devices
The surge in demand for home care and telemedicine has led to enormous market expansion of the medtech sector.
Major medtech organizations invest aggressively in innovating and building for next-generation products across the value chain. In such cases, medtech manufacturers need help maintaining quality control (QC) standards to match the diversified regulatory requirements across various geographies. Any discrepancy can result in unrecoverable financial loss and harm a manufacturer’s reputation. Adopting smart quality control standards will help establish a robust, consistent verification and validation (V&V) process across the manufacturing value chain. When used with real-time QC data acquisition and historicization methodology, advanced technologies such as AI, machine vision, and 5G will make way for a paperless validation process.
Innovation in smart quality control (QC) will enable medtech manufacturers to advance their businesses in untapped markets, outpace the competition, and implement an error-proof and compliant strategy. The patient-centric devices of the future should have a smart QC mechanism that can improve traceability, act on evidence-based data, and prevent the recurrence of past quality defects in near real time. This mechanism ensures that manufacturers produce high-precision, high-quality, and safe medical devices.
Medical device manufacturers are experiencing a significant shift in the industry toward building connected care devices that seamlessly integrate people, technology, and data, thus enabling the continuum of care. Enterprises want to augment their device portfolio with digital technologies to enhance patient journeys across care settings. Maintaining the highest quality control across these connected medical devices becomes critical in such a scenario.
Addressing business challenges with smart QC
Adopting smart QC will address a few key business challenges.
Ensuring process quality
Many medtech manufacturers manage their manufacturing process and business operations through integrated manufacturing execution systems (MES) and enterprise resource planning (ERP) systems. However, quality control is still often managed manually. The values that measuring instruments, such as a caliper, bore gauge, optical gauge comparator, and coordinate measuring machine (CMM), among others, provide are captured by the operator manually in a spreadsheet, and the data is recorded in the statistical process control (SPC) software for further analysis. This manual data capture process is tedious and error-prone.
Many measuring tools today can provide electronic output that makes it possible to connect with a programmable logic controller (PLC) or a computer, thus eliminating the manual entry of measured data. The automated data collection process eliminates the possibility of human error and maintains the desired quality standards with the help of real-time data analytics. Quality engineers can focus more on quality improvement strategies based on real-time data rather than spending time generating quality reports.
Figure 1: The real-time quality control process as envisioned with smart quality control.
Ensuring product quality
Medtech products are subject to strict regulatory protocols as ensuring quality, efficacy, and safety throughout the product life cycle is crucial. The QC process guarantees that the product performs as per the approved design, which the manufacturer records in the design history file (DHF) to further capture the necessary test protocols in the device history record (DHR). The design transfer process ensures that the test protocols are continuously followed through the device master record (DMR). Once the product passes the defined quality control checks, the manufacturer must capture the exact information, which remains part of the DHR, to be retrieved when required.
Some of the fundamental driving forces to build a robust and consistent QC process are as follows:
The market drivers and business benefits
A robust QC process improves the efficiency of manufacturing operations while adhering to good manufacturing practice (GMP) standards.
A consistent quality control process offers the following benefits:
Cost-effective operations: As per a market survey, the value of good quality medical devices equals 2-2.5% of sales, a significantly smaller value compared to the total liability involved in the cost of poor quality (which includes the intangible impact on business reputation, market share, among others). A robust validation process is required within the manufacturing quality control process with high traceability, which supports faster corrective and preventive action (CAPA) against any nonconformance by maintaining GMP.
Enhanced operational efficiency: The smart QC process brings in the right algorithms that provide human-interpretable information about anomalies in near-real-time. It can boost operational efficiency by 20-30%. Using technologies such as AI and robotics will additionally enhance the manufacturing cycle time.
Figure 2: Key market drivers and business value to medtech manufacturers
The paradigm shift: Why is it necessary
Different standards exist for product quality control inspections, and no defined process applies to all medical device categories.
Each step requires adherence to various quality control processes, from concept to prototype evaluation, raw materials specification to supplier onboarding, and manufacturing to finished products.
The American Society for Testing and Materials (ASTM) standards, International Organization for Standardization (ISO), and FDA guidelines define various quality controls in medtech manufacturing. However, based on different manufacturing landscapes (high volume and moderate or low volume), the quality control approach will vary.
We describe this further, considering two therapeutic segments:
Cardiovascular: The QC for a coronary catheter process verifies whether the balloon in the catheter inflates or deflects within the required limits in a particular environment. The operator has to verify the required dimension, elongation, or tensile strength with reference to the design specification, and the results are to be documented.
In another scenario, stents or guidewires can deflect at the desired angles during their pathway. Various transdermic or subcutaneous scenarios are being created by pushing through artificial arteries to measure tortuosity and frictional behavior. Stents and guidewires are verified by expansion and contraction throughout the process of bending and twisting within the pathway under test conditions.
Orthopedic: Various precise dimension checks are performed after each step of machining in an assembly router in the orthopedic implant manufacturing line. Quality engineers must identify material defects, sharp corners, nicks, and burrs through visual inspection for necessary corrections.
In each segment, there are two-fold challenges. On one side measuring and validating the quality processes involves various manual activities; conversely, the whole process heavily depends on the operator’s knowledge and skill sets.
Manufacturers are heavily dependent on manual processes, which are not aligned with the audit trail requirement. The possibility of false rejection will impact productivity. In addition, high cycle time will result in low throughput and productivity loss.
There is a need for an innovative autonomous quality inspection process – a shift from an individual-driven to a data-driven decision-making process. The cost of good quality will help establish consistent error-free products with high reliability and predictability across manufacturing lines in different geographies.