The Critical Role of Data Management Systems in Clinical Trials

The Critical Role of Data Management Systems
in Clinical Trials

Introduction

In the world of clinical trials, data is at the heart of the quest for safer and more effective treatments. However, as trials grow in scale and complexity, the data they generate from various sources has surged to unprecedented levels. Traditional data management methods are no longer sufficient for efficiently handling this deluge. This is where robust data management systems step in, playing a pivotal role in modern clinical trial success.

Historically, clinical data management relied on fragmented, manual processes and isolated data silos. Yet, in today’s data-driven landscape, where trials generate vast and diverse datasets, this approach no longer holds. Modern trials demand a shift towards advanced data management solutions.

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Centralized cloud-based data management systems

Enterprises are increasingly adopting centralized, cloud-based data management systems to meet these challenges. These systems serve as the central hub for data, offering a unified platform for seamless data integration. This integration fosters collaboration and facilitates real-time data access and analysis.

Enhancing efficiency through automation

Automation is another game-changing aspect of data management systems. By automating routine tasks like data entry and validation, these systems enhance efficiency, ensure data consistency, and expedite data management. In clinical trials, where data accuracy is paramount, automation is a game-changer.

Ensuring Data Quality and Compliance

Standardization and governance are crucial components of modern data management. Standardization ensures consistent data collection across sites and trials, simplifying comparisons and analysis. Governance, meanwhile, guarantees compliance with regulations and data security standards, safeguarding patient confidentiality and trial integrity.

Harnessing Real-Time Insights

One of the most transformative features of modern data management systems is their ability to provide real-time analytics. Researchers and sponsors can access and analyze data as it is generated, enabling swift, informed decisions. This empowers them to refine protocols, optimize patient recruitment, and accelerate therapy development.

In conclusion, data management systems are now indispensable in clinical trials. They not only streamline data processes but also unlock data’s full potential. As trials become increasingly data-centric, these systems are pivotal in advancing medical research, ensuring data accuracy, and contributing to innovative treatments. In an era where data holds paramount importance, data management systems stand as the cornerstone of clinical research.

Revolutionizing Aircraft Maintenance with Digital Twins

Revolutionizing Aircraft Maintenance
with Digital Twins

How Technology is changing the Aviation Industry

Introduction

Airlines will continue to adapt to the evolving new normal, operate under strict budget constraints, and prioritize cash preservation to tackle the uncertainties and challenges. So, maintaining the aircraft at optimal operation levels is critical to run the airlines.

In spite of being new generation aircraft and having efficient and longer lasting engines, the cost of maintenance continues to increase due to shortage of resources, scarcity of spare parts of older aircrafts, and inflation. As such, airlines are shifting attention towards leveraging the latest innovative technologies, which were not widely available in the recent past, to tackle increasing challenges in maintenance operations. Among these latest cutting-edge innovative technologies, digital twin is playing a critical role in the space of aircraft maintenance.

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Digital Twin (DT)

A digital twin refers to a computer-based replica of a tangible entity, system, or operation that exists in the physical world. However, it is more than just 3D models. Digital twin implements all of the data and models required to accurately represent the different aspects of a product or process in order to recreate how the product and process will behave in a changing environment in the real world. A critical prerequisite of the digital twin notion is that it must be a dynamic and a constantly updated representation of the real product, or process in question.

As per E. Glaessgen and D. Stargel “A Digital Twin is an integrated multiphysics, multiscale, probabilistic simulation of an as-built vehicle or system that uses the best available physical models, sensor updates, fleet history, etc., to mirror the life of its corresponding flying twin”

Aircraft Maintenance and Digital Twin

Not all components/parts in an aircraft are good candidates for a digital twin. As implementation of DT is complex and costly, it is important to focus on parts/processes that are critical to business operation and will provide ROI. An aircraft has multiple components, and so, only a few qualify as candidates for DT e.g., engine, landing gear, hydraulic system, fuel system, and aircraft body.

Digital twin applies multiphysics and multiscale modeling techniques along with AI/ML models, which analyzes the behavior of aircraft components in different electrical, thermal, mechanical, magnetic, and chemical conditions. The sensors generate datapoints and the models perform the what-if analysis, which captures how different components individually and as a whole will behave in different conditions without changing the properties of the physical aircraft components.

Below is the illustration of the DT of aircraft and fleet:

The Digital Twin Advantage

Transforming maintenance
By collecting data generated by IoT sensors installed in the aircraft parts, digital twins along with AI/ML analytics models can forecast unscheduled maintenance. Additionally, digital twins can also predict the conditions when the parts/component could fail. By providing prior insights into the status of the aircraft components, digital twins facilitate early detection of a problem.
Increased safety
Leveraging digital twins and combining AI/ML enabled predictive analytics can assist in the earlier detection of a problem by capturing prior insights of the status of the aircraft components. The end result is an improvement in safety, which ultimately makes air travel safer and more reliable.
Lower financial impact
Digital twin enables the operator to predict probable maintenance failures before the breakdowns can occur. It gives lead time to the operator to minimize the downtime, increase aircraft utilizations, and profitability. By replicating the model in Digital twin, air carriers can forecast maintenance costs.
Improved supply chain
With the application of digital twin, operators can manage the inventory more effectively by appropriately ordering the parts that would fail as forecasted by the analytics model.
With advanced technologies like Digital Twin, aircraft maintenance has become even more effective and it is impacting the aviation industry significantly. To learn more about innovative technology in aviation, visit https://aviation.tcgdigital.com/digital-transformation/

References

Challenges of Migrating Legacy Applications to AWS

Challenges of Migrating Legacy
Applications to AWS

Introduction

In a world of rapidly changing technology, many organizations still rely on legacy mainframes to keep their most critical operations running. These age-old systems have been tuned and customized to meet the functional requirements of the business, and as a result, have become locked-in to vendors over the years. However, maintaining and supporting these systems can be a challenge, as resources are scarce, and the lack of an integrated testing environment can limit flexibility, add risk, and increase test time. In addition, legacy technology can encounter problems with maintenance, support, improvement, integration, and user experience.

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Recently my team and I were discussing how to help our clients unlock the value of their industrial and manufacturing data. These industries often wrestle with terabytes of time-series data from a myriad of sensors, machines, processes and external sources. Each data source could potentially include different features with various formats, have non-rationalized time intervals and be generated from various proprietary technologies. The challenge of making this data available on a platform where workers can exploit the data and discover its hidden value can be overwhelming. Here is where the vision of AI Democratization often hits its first significant roadblock.

Managers who are tempted to feel elated at the prospect of having access to all the data they could ever wish for, soon realize it is a data sword of Damocles* hanging by a thread, ready to snap and bury them if they can’t find a way to unlock its value.
Richard Westall’s Sword of Damocles, 1812
* The parable of the sword of Damocles teaches us that no matter how good someone’s life may appear, it’s difficult to be happy living under existential threat.

So, what's the solution?

The answer lies in application, information, and data migration. By migrating to the cloud, organizations can improve their operational efficiency, reduce IT costs, improve performance, and take their business to the next level. Modern technology solutions can introduce automation to manual processes, which are prone to errors, and enhance reporting and rich featured UI and rules engine, allowing businesses to manage data more efficiently, and changes will be reflected in real-time.

The ultimate objective

The ultimate objective is to sunset the legacy system with minimal disruption to the business and transition towards a more robust and scalable information technology platform to support current and future business needs in a cost-effective and collaborative manner. This also involves designing a common technology platform for operational applications to minimize data redundancy, decrease the cost of building, integrating, and maintaining new and existing applications.

However, migrating from legacy mainframes to modern technology solutions is not without its challenges.
The key challenges during the migration process includes:
  • Rewriting application architecture for the cloud
  • Complexity of the integration of data, systems, and processes
  • Compliance and security
  • Dealing with hybrid networking setups
  • Investing in people and tools needed to migrate successfully
  • Training users on the new systems
To overcome these challenges, businesses need to have a clear set of guiding principles in place.
Consider these solutions and guiding principles:
  • Create a reference architecture for the legacy application to migrate to a cloud-native architecture on AWS.
  • Compliance & Security, Hybrid connectivity – AWS Accounts/VPCs, including TGW, Direct Connect Gateway, multi region peering, Landing Zones, VPCs AZs Subnets, Security Groups, IAM role
  • Data Security – Encrypted at Rest (AWS KMS), Encrypted at transit (SSL/TLS)
  • Real Time Transactions and Streaming, Messaging Integrations– SNS, SQS, MSK, Kinesis
  • Adapters – On-Prem to cloud protocol bridge
  • Use Serverless components/services as much as possible – Lambda, StepFunctions for workflow
  • AWS API Gateway – Lambda functions are invoked through API Gateway
  • Computation – Application container in EKS
  • ALB – EKS pods are invoked using ALB
  • AWS Secret Manager – Store credentials securely

In conclusion, the migration from legacy mainframes to modern technology solutions, such as AWS, is no longer an option but a necessity for businesses that want to remain competitive and agile. While the migration process may seem daunting, it can be successfully achieved with careful planning and execution, along with adherence to guiding principles. By leveraging AWS’s cloud-native architecture and services, organizations can improve operational efficiency, reduce costs, and enhance their overall competitiveness. With the right strategy and tools, the migration journey can result in a more robust and scalable information technology platform that meets current and future business needs.

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Optimising aircraft turnaround time-a TCG Digital service offering

Optimising aircraft turnaround time
-a TCG Digital service offering

Introduction

Optimising aircraft turnaround time is a critical task for airlines looking to maximise efficiency and minimise costs. Delays in turnaround time can lead to lost revenue opportunities, as well as increased costs associated with aircraft operations. According to industry estimates, up to 15% efficiency can be achieved in current turnaround processes and technologies.

One of the most significant contributors to turn around delays is refuelling, accounting for a whopping 56% of all such delays. The typical cost for turnaround operations for a B737 is $70/hour.The good news is that a 25% uplift in refuelling efficiency can reduce turnaround time (TAT) by up to 3 minutes, which can translate into significant cost savings for airlines.For airlines with a fleet size of around 500 aircraft, reducing cycle time by 4-6 minutes can free up 2-3% of the fleet, potentially leading to cost savings of between $30-75M through TAT optimisation.

But how can airlines achieve these efficiencies? Our breakthrough solution for TAT Optimization offers significant benefits to both airlines and airports. By reducing the cost of operations and minimizing ground time, our solution enables better aircraft utilization and provides opportunities for airlines to operate on newer routes, ultimately leading to increased revenue opportunities for both airlines and airports. It utilises real-time feeds from airport cameras at gates, analysing video feeds in real-time through advanced AI/ML algorithms over a scalable cloud platform. The system analyses moveable and immovable objects on the tarmac, such as luggage carts, trolleys, cargo, fuel trucks, tugs, catering trucks, cleaning staff and equipment, and other objects, to determine turn events that could delay TAT. The system also generates pre-configured alerts and notifications to enlisted subscribers. It provides true Omni channel customer experience via state of the art dashboards

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Unlocking Value from Industrial Data

Recently my team and I were discussing how to help our clients unlock the value of their industrial and manufacturing data. These industries often wrestle with terabytes of time-series data from a myriad of sensors, machines, processes and external sources. Each data source could potentially include different features with various formats, have non-rationalized time intervals and be generated from various proprietary technologies. The challenge of making this data available on a platform where workers can exploit the data and discover its hidden value can be overwhelming. Here is where the vision of AI Democratization often hits its first significant roadblock.

Managers who are tempted to feel elated at the prospect of having access to all the data they could ever wish for, soon realize it is a data sword of Damocles* hanging by a thread, ready to snap and bury them if they can’t find a way to unlock its value.
Richard Westall’s Sword of Damocles, 1812
* The parable of the sword of Damocles teaches us that no matter how good someone’s life may appear, it’s difficult to be happy living under existential threat.
The solution landscape

The backbone of TCG Digital’s solution is built on AWS infrastructure. Video feeds from gate cameras at airports are captured using AWS IoT Core and published onto Kinesis Video Stream. The Orchestrator running on ECS Fargate consumes the videos and uses a pre-trained inference model running on an EC2 instance to generate turnaround events. It then publishes those events onto a Kinesis Data Stream. A Lambda function consumes these events and mutates them to an AppSync API to be displayed on the turnaround dashboard. A rules engine built using Step Function analyses the events and raises alerts in case of any potential delays.

In conclusion, TCG Digital’s TAT optimisation solution is a game-changer for airlines looking to improve efficiency, reduce costs, and enhance the passenger experience. By reducing turnaround time, airlines can increase revenue opportunities, operate more efficiently, and provide a more seamless travel experience for their passengers.

The solution backbone