Solving the mystery of named resource management in life sciences project management for organizational effectiveness

A pharma success story: How a generative AI chatbot helped in driving swift query resolution in clinical trial

On average, it takes over 10 years and costs upwards of $2.6 billion to get a new drug from initial discovery to approval by regulatory bodies like the FDA. Moreover, processes like clinical trials are long, complex, and expensive that pharmaceutical companies must undertake to test the safety and efficacy of new medical treatments. A major factor behind these daunting timelines and costs is the organizational challenge of coordinating and managing thousands of human participants across multiple research sites during trials that can last months or years. Manual and repetitive administrative/training tasks become immensely tedious to cope with. This inevitably leads to inefficiencies that inflate costs and delay results. Let us bring you a real-time example of how a pharma company embraced the power of generative AI to streamline their clinical trial operations. With over 500 active clinical studies spread across the country, the Research Pharmacists (RPs) were spending at least 50% of their time handling queries from the study teams. Most of these queries were repetitive and hindered the RPs productivity in the other crucial areas of the study. The project leader opted to re-engineer the clinical trial operations by including robotic process automation, and bots to not only make the process efficient, but also bridge the knowledge gaps between the study team training and patient enrollment. Administrative tasks which were repetitive and taking up a lot of time were identified and were first in line to either get automated or handed over to a bot. Initially, the bot was challenged by the RPs on how it could effectively answer the study team’s questions. Also, they were skeptical regarding the process of redirecting any out-of-the-manual queries or escalations which required immediate attention. Generative AI Bot Intervention in Clinical Trial Operations Interactions between study teams and research pharmacists are a crucial aspect of ensuring the smooth progress of trials. Study teams and RPs often establish clear communication channels early in the trial. They mutually exchange information which includes details such as the drug's mechanism of action, formulation, dosage, administration protocols, and any unique considerations. The study team may enquire about proper storage, preparation, dispensing if methods are unclear, appropriate documentation practices. With handling over 500 clinical sites, the RPs were constantly getting tons of questions from different study teams. Though most of these questions were repetitive, timely responses were required for the smooth functioning of the clinical trial process. i2e Consulting was engaged to design a solution using which repetitive queries could be answered on behalf of the RPs. The Pharma client also wanted the solution to be capable of redirecting escalations and out-of-the-manual questions to the respective RP for immediate attention. Implementing the Gen AI Chatbot: Challenges & Accomplishments There were two challenges in front of team i2e, (1) to identify the repetitive questions directed towards the RPs, and (2) to design a process to handle any out-of-the-manual queries. Team i2e developed an advanced chatbot leveraging Amazon SageMaker’s generative AI capabilities along with a wrapper around Kore.ai to build a user friendly chatbot interface capable of answering queries pertaining to Investigational Product (IP). Utilizing sophisticated prompt engineering capabilities resulted in enhanced performance and efficiency in delivering precise responses. The backend web platform was built to store and process the vast IP manual documents and direct user’s inputs to relevant responses and escalations. The team also built a notification system which triggers emails to the CRPs in case of out-of-the-manual questions or escalations. Result? A significant reduction in repetitive queries, and 2X expedited query response, most importantly, the CRPs were able to invest their time in other crucial areas of the clinical trials, and the study team was able to clear off their questions instantly which contributed to the smooth progression of the clinical trial. The gen AI chatbot was a critical piece of the puzzle the client was trying to solve. The Clinical Research Coordinator wanted to plug the knowledge gaps resulting in repetitive questions directed towards the RPs. With the chatbot recording the questions and their answers, it became a central repository to identify knowledge gaps and bring about changes in the IP manual and the training modules. Expanding the Chatbot Footprint After successful implementation in two therapeutic areas, the project leader then expanded the chatbot to clinical trials in other areas. The solution designed was easy-to-deploy and had the scalability to include more clinical trials teams, and still delivered a similar output. The Future of Generative AI in Clinical Trails The possibilities of AI/ML do not end with chatbots, it can be extended to monitoring patient health. Here are a few areas where Gen AI can increase precision and productivity in clinical trials. Monitoring patient health and compliance Keeping human trial participants closely engaged and supported is crucial for productive trials. However, regular check-ins and counseling on a global scale has traditionally strained staff bandwidth. AI chatbots present a scalable solution, acting as always-available virtual health assistants. Integrating seamlessly into messaging apps people already use daily, bots can automatically check symptoms, deliver health information, manage medication intake alerts, collect progress self-reports, offer motivating behavioral interventions, and more. Working around the clock at marginal cost, they can provide responsive support with more reliability than overworked nurses across scattered trial sites. Bots further enable continuous remote patient monitoring to improve compliance rates that directly impact trial integrity. By establishing ongoing dialogue at scale, they also facilitate early detection of adverse reactions or mental health issues so coordinators can rapidly respond and keep participants engaged. Extracting powerful insights from trial data The data collected across a multi-year clinical trial is vast and complex, usually amounting to terabytes of medical records, genomic sequences, imaging scans, biomarker assays, questionnaire responses, and more. Manually combing through such immense datasets using legacy analytics tools is just not feasible. This is where generative AI truly shines, capable of intelligently parsing mountains of structured and unstructured data to uncover subtle patterns that lead to actionable insights. As natural language models, chatbots can further analyze doctors' notes, patient messages, and open-ended survey responses. Generative AI promises to transform every facet of clinical trials, from participant engagement to research analytics and everything in between. Chatbots and other models like GPT-3 mark an exciting shift toward cloud-based software that keeps getting smarter, allowing pharmaceutical experts to focus on innovation and strategy rather than getting bogged down in manual processes.

Project Online and Power BI- A Dynamic Duo for Making Reports That Matter

Is making reports taking up all your time? Or Are you still wondering the answers to questions such as ‘what is the project’s progress? Or ‘how much will this project cost the company after two years?’ then your business needs a digital makeover. Companies need applications that can quickly analyze huge data sets and come up with trends that can help in decision-making. This is where Project Online and Power BI come into play. In this blog, we will tell you about Microsoft Project Online and Power BI, and how they can become a game-changer for your business? These applications are powered by Microsoft, and i2e can help you with the implementation as well as migration of your existing projects. Are You Already Using Project Online? Along with being a magnificent project management application, Project Online is also a precious data source. Leverage it correctly and it can give a powerful start towards making meaningful reports. This is where Power BI can change the way you look at the data. But doesn’t Project Online come with a reporting module, then why should you integrate Power BI? This is a reasonable doubt, which many of our clients expressed. Read the next section to find out. Why Integrate Power BI to Project Online? Power BI is a reporting tool that can analyze data and convert it into meaningful metrics for the business. Yes, Project Online does generate reports, but if you need customized reports, along with actionable insights, and smart visuals, then Power BI is what you need. Using Power BI, companies can do more than just creating reports, they can dig deep into the data and use the Machine Learning algorithm to predict trends. The best part is you can easily integrate Power BI to Project Online and eliminate the hassle of exporting data and manually generating reports. Integrating Power BI to Project Online will boost your reporting capabilities and help in smart decision-making. Power BI’s Components Using Power Q&A, you can create visuals by just typing in questions. For example, ‘who owns more projects,’ or ‘how many projects are owned per owner.’Power BI has a Power query option which can structure your data. Once the data is structured, the Data Management Gateway refreshes the data periodically and the new data will follow the same format, saving you time and effort.Power BI also comes with a Quick Insights feature which can churn your data and create subsets to give you valuable insights. For example, it can give you visuals of which project might cost more, or which project can fall out company’s goals in the future.There are other components such as the Power View and the Power Map, the former comes with an easy drag-and-drop interface, and the latter is a 3D geospatial data visualization tool. Both these tools help in creating superior reports. Along with creating impeccable reports, Power BI can accumulate data from various data sources, create visuals and share across global data centers. This helps companies to meet their compliance and regulatory needs. Power BI- The Game Changer Fetch data from various cloud services – helps you in making consolidated reports.Build smart dashboards- gives a holistic view of the business empowering teams to make informed decisions.Ask questions and get real-time answers- gives answers in the form of a graph or chart for quicker understanding.Scan hidden insights in seconds- never miss out any data or trend which can be helpful for the business.Secured live access from any device- easy to access through Power BI mobile apps. If you are looking for a way to make smarter reports, then it is time to adopt artificial intelligence tools that can pull data and allow you to visualize in your own way. If you need assistance in implementing Project Online and Power BI, connect with us. Our team of experts will understand your requirements and provide you with the right solution.

Resource Management in Life Sciences: Digital Transformation for Increased Efficiency

The life sciences industry is an ever-evolving space wherein efficient resource management is critical in ensuring successful execution of R&D projects. Organizations need to grow and maintain a balance between resource allocation and changing demands of projects. As multiple projects go through a series of stages, challenges like budget constraints, limited resources and visibility, and unpredictable timelines start hindering the flow of projects. Without a strong strategy, life sciences companies can experience cost overruns and miss deadlines. To sustain such a dynamic industry, adopting digital solutions that enable seamless collaboration, demand forecasting, and resource visibility is essential. Let’s explore the importance of resource management in R&D projects using digital solutions to optimize resources. Importance of Resource Management in R&D PPM Demand management and resource allocation plays an important role for the following reasons: Balancing available resources with the ongoing demand of projects helps life sciences companies prevent issues like underutilization and lack of resources. It even ensures on-time delivery while maintaining project momentum. When there’s a shortage of resources, effective resource management helps to focus on projects that need critical attention and those of high value. It is essential to assess various scenarios when planning for effective resource management to make informed decisions without disturbing the organizational flow. Aligning resource availability as per the company’s strategic objectives including cost efficiency and innovation is important to support overall organizational goals. Factors Contributing to Resource-Demand Mismatch in R&D PPM Understanding the factors that cause a mismatch between resource allocation and demand management helps to develop strategies to develop the company’s project goals. Unpredictable project timelines: Projects in pharma companies overlap concerning the timelines. One delay could disrupt the flow of other projects, creating more challenges. This concern scrambles critical projects and could lead to other unannounced issues in the company. Inaccurate demand forecasting: Misinterpreting resource requirements due to incorrect data is a common issue. Life sciences organizations face mismatches between project needs and resource availability due to fluctuations in shifting market conditions or project complexities. Limited resources visibility: Teams cannot function or plan ahead without precise real-time data. When every team works their way without collaboration, projects may expect misallocations and inefficiencies. Budget constraints: Not having sufficient funds to scale resources during high demand creates several hurdles along the way. Additionally, further cuts in R&D budgets can leave the team overburdened with tasks at the rate of lesser funds. Change in priorities: Responding to the change in market trends is inevitable in life sciences organizations. However, no prior planning can lead to project complexities and may require making too many last-minute adjustments. Inefficient resource utilization: Imbalance in the team occurs when resources are not utilized as per their need. Low-priority tasks get the resources, and the high-value projects get no right resources. External dependencies: Most companies often miss out on this issue that occurs due to dependency on external agents, be it CROs, suppliers, or external partners. This can delay not one but several projects in line. Lack of PPM tools: Without a unified integrated platform, projects tend to dissemble. Resources, portfolios, and project management don’t align together, leading to inefficiencies and wasted opportunities. Key Strategies for Effective Resource Management Implementing strategies can bridge the gap between resource allocation and demand management in R&D Project and Portfolio Management. Demand forecasting accuracy Implementing advanced analytics can improve accuracy of demand forecasting using real-time insights. By analyzing changing market conditions and historical data, resource demands can be predicted to make informed decisions at the right time. Budget allocation It’s essential to prioritize resources based on the tasks and timelines. High-value projects should get the resource support first-hand; while ensuring they do not face hurdles due to shortage of resources. This strategy also avoids the use of too many resources on low-priority projects. Resource visibility tools in real-time Implementing the right PPM tools plays a significant role in providing real-time insights into resource allocation and availability. This strategy helps teams to function seamlessly, thereby minimizing inefficiencies and allocating resources as per project priorities. Cross-functional collaboration In life sciences organizations, working in silos wouldn’t fetch the required results. There should be collaboration among departments to understand dependencies on the projects. By knowing so, risks can be managed well without impacting project timelines, leading to effective resource allocation. Prioritization frameworks Organizations need to prioritize projects as per their potential impact and strategic alignment with the overall goals. Hence, portfolio reviews should be done regularly to identify which projects need to be halted, discontinued, or deprioritized. Based on the review, resources can be well allocated as per their actual needs. Project portfolio management (PPM) tools Every life sciences company should have an integrated PPM solution that not only aligns with projects and portfolios but also with resource management. A unified approach helps in planning better, executing as per the plan, and monitoring to result in reduced opportunities and enhanced efficiencies. Effective resource management is essential to drive success in R&D PPM in life sciences organizations. However, without the right strategies, project delays and missed opportunities are inevitable. Adopting and implementing strategies like real-time resource visibility, cross-functional collaboration, and demand forecasting help in reducing efficiencies, mitigating project delays, and using resources where they are required most. All these solutions streamline functionalities and minimize bottlenecks. Overall, resource allocation alignment with company’s goals improves overall success of the project and fosters innovation. To know how your company can make the best use of resource management strategies, connect with the experts at i2e Consulting and get customized solutions as per your requirements.