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Nihar Routray BLP022 Solving the problem of disjointed information and high R&D costs

Cloud Computing and Analytics in Pharma

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Solving the problems of unstructured data and high R&D costs in the pharma industry through the use of Cloud computing and Analytics

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Page 1: Cloud Computing and Analytics in Pharma

Nihar Routray

BLP022

Solving the problem of disjointed information and high R&D costs

Page 2: Cloud Computing and Analytics in Pharma

The Challenge Need for a practical solution to tackle the twin problems of disjointed information and extremely high R&D costs for a multi-national and multi-brand company.

R & D in a pharmaceutical company is a very complex process requiring considerable amount of time and a diverse set of stand-alone systems and specialized computer applications. The requirement of resources for these applications has become so high now that the company cannot afford the considerable costs of building, implementing and supporting these infrastructures.

Pharmaceutical companies generally face the problem of having complex silos of information built around their brands. Along with that large amount of information is being created everyday by numerous systems and applications in all kinds of formats which pose a serious challenge to manage, monitor and retrieve required information at times of need.

Being a large multi-national, though the company employs advanced communication systems but still a significant disconnect is observed between the various enterprise teams as they are dispersed across different global locations.

Pharma companies also need to maintain their legacy systems containing critical data as the FDA requires data related to a drug to be maintained for a minimum period of 2 years after it was last sold. Due to this the legacy systems cannot be completely done away with and integrating them will run into huge costs.

Assumption: Have considered a pharmaceutical company which is spread across different geographies across the world and has multiple brands in its drug portfolio

Page 3: Cloud Computing and Analytics in Pharma

Current Situation Currently, the company is just throwing in more resources, people, computational and storage capabilities at the problem. However, this approach cannot be continued with and is economically unviable in today’s world of cut-throat competition and economic climate. Now let us understand the R&D process and how IT has been supporting it.

DISCOVERY Pre Discovery Aim: Understand the disease and choose target molecule Process: Scientists from government, industry and academic institutes create

knowledge base using various computational tools and insights

DEVELOPMENT

Discovery Aim: Find Lead compound Process: High Throughput screening via robotics and computational power, De

Novo creation, Genetic engineering Pre-Clinical Aim: Determine drug is safe for testing in human beings Process: Extensive in vitro and in vivo tests and recording of test data

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IND Aim: Obtain approval from FDA for clinical trials in human beings Process: Review by FDA and IRB Clinical Trials Aim: Trials in human being to check drug efficacy, dosage and safety Process: Drug tested on human beings in 3 phases moving from smaller to

larger patient groups. Trial data recorded on paper or through LIMS

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Review Aim: Review by FDA for drug approval and manufacturing Process: FDA reviews the NDA which can be more than 100000 pages Manufacturing Aim: Large scale manufacturing of drug Process: Scaling up facility and large scale production following GMP

Ongoing Studies Aim: Monitor drug in market Process: Monitor the drug in market and report adverse events to FDA Estimates Cost: Upto 1 Billion Duration: 10-15 years

Page 4: Cloud Computing and Analytics in Pharma

All the steps mentioned above include a huge number of activities and consume a lot of time to get completed. A variety of dedicated systems are employed at each stage to support processes and record and manage the data being generated. As we saw in the process flow, a new drug development costs around $1 billion and takes a minimum of 10 years to complete. Also, a large number of potential drug research projects are shelved at some point during the drug development process owing to adverse effects or limited efficacy. According to Industry records, only 1 out of 1,000 potential compounds get approved finally and are sold in the market. The company is currently getting inundated with complicated and resource intensive applications which are churning out huge amount of data. So, the company is hard pressed to do more with less while increasing flexibility and responsiveness to meet the business needs. The IT budgets of Pharma companies are nearly consuming 15% of the total R&D expenditures and about 8% of the total headcount of the organization. This high level of resource consumption while maybe essential but does move the organization away from its core mission of drug discovery and development. So it becomes highly imperative for the company to find ways to reduce R&D costs while at the same time increasing productivity through better data management and retrieval.

Approach Highlights Happiest Minds proposes a two pronged approach of embedding analytics into its daily operations while leveraging the cloud to counter the problems of disjointed information and high R&D costs. This approach would be carefully implemented along with an information agenda as it would provide a high level roadmap aligning the business needs with the analytic insight and the cloud platform to the underlying technology and processes.

The company will be provided with an access to a low-cost shared cloud computing environment with an array of hardware, software and technical resources which would help reduce the various costs. Our cloud platforms will help you integrate your entire business services and include high levels of shared data management and advanced features to help you adopt new business models which would clearly differentiate your organization from the rest in

Page 5: Cloud Computing and Analytics in Pharma

the industry. These cloud platforms are also encompassed in a layer of security framework which would take care of all the perceived risks. There would be further reduction in costs as all the heavy functions such as computing power and storage will be leveraged in the cloud.

Proportion of Life Sciences R&D Informatics budget devoted to Cloud computing in 3 years:

Source: Insight Pharma Reports

The augmented analytics capabilities provide end users access to near real-time information facilitating collaboration and preserving transparency. The differentiated analytics advantage provided by Happiest Minds will help the company achieve value creation quite early in an organization’s progression to sophistication by leveraging structured and unstructured data from within and outside the organization.

Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute for Business Value study.

Copyright © Massachusetts Institute of Technology 2010.

Page 6: Cloud Computing and Analytics in Pharma

Why Happiest Minds Companies are seizing this opportunity provided by Happiest Minds to use advanced information analytics and cloud computing for business advantage in their respective industry sectors. These business leaders are not depending anymore only on intuition but are combining the new analytics techniques with the expertise from Happiest Minds to make decisions in a completely different way.

Creating disruptions through technology as well as through the next generation skilled worker