In the rapidly evolving biotech industry, manual analysis of DNA/RNA plates is often time-consuming and prone to errors, leading to costly delays and increased operational expenses. A 2021 study highlighted that errors in genetic sequences have compromised the integrity of numerous studies, emphasizing the need for more accurate and efficient analysis methods.
To address these challenges, a leading biotech firm collaborated with Working Excellence to implement a machine learning solution aimed at minimizing errors and streamlining the analysis process.
Introduction
The biotech sector operates under relentless pressure to deliver precise, reliable results—often under strict timelines and high regulatory scrutiny. At the heart of many research and diagnostic workflows is the process of DNA/RNA plate analysis, where even the smallest error can have outsized consequences. Inaccuracies might compromise experimental validity or delay crucial milestones, ultimately inflating project costs and time-to-market for new therapies. As competition intensifies and global demand for innovative healthcare solutions continues to rise, the stakes for efficiency and accuracy have never been higher.
In this environment, manual DNA/RNA plate analysis is a critical pain point. Relying on human labor introduces a margin of error that can escalate quickly, especially when teams handle large volumes of samples or operate under tight turnaround times. Beyond the inherent risk of human missteps, manual methods also drive up labor costs and slow down overall throughput, which can impede a biotech organization’s ability to stay agile and competitive.
Recognizing these challenges, a prominent biotech company automated its analysis process. By transitioning away from manual workflows and embracing cutting-edge technology, they aimed to enhance the precision of DNA/RNA plate analysis while reducing labor-intensive tasks. The goal is to minimize errors, accelerate throughput, and ensure that their valuable research and development efforts consistently meet the highest standards of quality and efficiency.
Problem Statement
In the biotech landscape, precision isn’t just an ideal—it’s an absolute requirement. Whether pioneering novel therapies or refining diagnostic procedures, any level of inaccuracy can have reverberating consequences. This is especially true when it comes to DNA/RNA plate analysis, where even a minor oversight can undermine valuable research findings. In this high-stakes environment, one biotech company found itself contending with significant challenges that impaired both accuracy and efficiency, threatening to erode its competitive edge.
At the heart of these obstacles was a reliance on traditional manual methods and underperforming automated systems. The manual workflow not only demanded intensive human labor but also introduced inevitable human error—an unacceptable risk when dealing with intricate genetic materials. Meanwhile, existing robotic technology often missed crucial steps, triggering rework and added delays. Facing a growing demand for faster, more reliable results, the company realized its existing systems were no longer sustainable.
Compounding these limitations was a broader issue of operational inefficiency, where unplanned project extensions and escalating costs limited the organization’s capacity for innovation. By repeatedly correcting mistakes and rerunning analyses, the company lost valuable time and resources. Recognizing that incremental fixes were insufficient, the leadership decided to confront these systemic problems head-on, aiming to revolutionize its approach to plate analysis and set new standards for quality and performance in the biotech sector.
Manual Analysis Errors
Despite the organization’s best efforts, traditional manual inspection of DNA/RNA plates remained highly prone to human error. Lab technicians were required to scan plates visually, often at high volumes and under tight deadlines, making slips virtually inevitable. Such inaccuracies not only undermined the integrity of critical datasets but also risked misinforming subsequent research decisions, thereby inflating costs and delaying breakthroughs.
Robotic Inaccuracies
While automation was in place, the current robotic systems presented their own set of complications. Frequently, these machines missed wells or recorded them incorrectly, forcing teams to refill and reanalyze entire plates—an expensive, time-consuming process. Rather than streamlining the workflow, the robots’ deficiencies introduced unpredictability, compounding the very challenges they were intended to solve.
Operational Inefficiencies
A convergence of manual errors and inconsistent robotic performance led to project overruns, escalating expenses, and inefficient use of laboratory resources. As each mistake triggered rework, the organization’s ability to deliver timely results to stakeholders diminished, jeopardizing both short-term milestones and long-term strategic goals. Faced with mounting pressures in a competitive marketplace, the company recognized that failing to address these operational inefficiencies would hamper innovation and erode its position as a leading biotech player.
Engaging Working Excellence: Finding the Right Partner:AI Solution for Biotech
When faced with persistent inaccuracies and the strain of labor-intensive workflows, this biotech company recognized the urgent need for a strategic partner equipped to overhaul their entire approach to DNA/RNA plate analysis. Working Excellence emerged as the clear choice, pairing a deep technical skill set with a proven ability to deliver AI-powered transformation in highly regulated, data-rich environments. By taking a holistic look at the existing workflow, the team pinpointed precisely where automation and machine learning could streamline processes, enhance accuracy, and reduce operational costs. This approach formed the backbone of a solution that tackled each pain point head-on:
Development of a Deep Neural Network Model
Drawing on the power of Keras, Working Excellence devised a cutting-edge deep learning model that redefined how plate data was processed. This advanced system minimized human intervention, sharply reducing errors and freeing technicians to focus on higher-value tasks.
Creation of a Custom Labeling Application
Using React.JS and .NET Core, the team built a tailored application that seamlessly integrated with the newly trained model. This robust platform not only streamlined data labeling and asset management but also laid the groundwork for future scalability as the biotech company continued to grow.
Enhanced Feature Engineering and Regularization
By refining input variables and applying sophisticated regularization techniques, Working Excellence ensured a high degree of accuracy in automatically classifying plates as empty, non-empty, or tilted. This level of precision drastically reduced misclassifications, saving both time and resources in day-to-day operations.
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Immediate Value Creation Through Technical Improvements
Needs Assessment
By conducting a deep dive into the existing DNA/RNA plate analysis workflows, our team swiftly uncovered the most pressing inefficiencies. This crucial first step set the stage for targeted solutions that would streamline processes and enhance data integrity right from the start.
Model Development
Leveraging Keras, a cutting-edge deep learning framework, we rapidly built a powerful neural network model tailored to the client’s unique requirements. This model significantly heightened the precision of plate status classification, delivering immediate gains in accuracy.
Application Development
In parallel, we created a custom labeling application using React.JS and .NET Core, ensuring a seamless interface between the newly developed model and existing systems. This integration accelerated the data labeling process, bringing tangible time savings early in the project.
Feature Engineering
Our team applied advanced feature engineering and regularization methods to refine the model’s reliability. By optimizing classification accuracy for empty, non-empty, and tilted plates, the client instantly experienced reduced errors and rework—key drivers of operational cost savings.
System Integration and Testing
Finally, we wove the model and application into the client’s broader workflow, conducting rigorous tests to guarantee maximum robustness and efficiency. This end-to-end validation ensured a smooth handover and immediate value realization, minimizing downtime and maximizing ROI from day one.
Results and Benefits
By the Numbers:
50% Reduction in Manual Analysis Time
Automation significantly decreased the time required for plate analysis, allowing for faster project completion.
70% Decrease in Plate Refilling Rate
40% Improvement in Operational Efficiency
Qualitative Benefits:
Enhanced Data Accuracy: The integration of machine learning reduced errors, leading to more reliable data for decision-making.
Resource Optimization: Automation allowed skilled personnel to focus on more complex tasks, improving productivity.
Competitive Advantage: The implementation of advanced technologies positioned the company ahead of competitors in process efficiency.
Lessons Learned
Strategic Integration of AI/ML: Incorporating machine learning solutions requires careful planning and alignment with existing workflows to achieve desired outcomes.
Importance of Custom Solutions: Tailored applications, such as the custom labeling tool, are crucial for meeting specific operational needs and ensuring seamless integration.
Continuous Improvement: Ongoing evaluation and refinement of AI models and processes are essential to maintain efficiency and adapt to evolving challenges.
Looking Ahead
By partnering with Working Excellence, the biotech firm successfully transformed its DNA/RNA plate analysis process through the integration of machine learning and custom applications. This collaboration not only enhanced operational efficiency but also set a benchmark for leveraging AI/ML solutions in the biotech industry.
Explore how Working Excellence can revolutionize your biotech processes with cutting-edge AI and machine learning solutions. Contact us or request a demo today!