This blog discusses latest trends and the role technology plays in the life sciences industry. It focuses on Infosys life sciences services and solutions and how they can help accelerate business.

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November 18, 2015

Predictive approach to 'Quality' in clinical trials



  Authors:  Deepak P.N., AVP - Principal Technology Architect; Pooja Durgad, Senior Associate Consultant; Renuka Natarajan, Senior Associate Consultant


Quality is not an act. It is a habit ~ Aristotle

A recent engagement with the clinical trials quality team of one of the top 10 pharmaceutical companies, located in North America, gave more insights to the way sponsors handle and manage the risks throughout the lifecycle of a typical clinical trial. Quality Risk management or QRM is the process of proactively identifying risks, prioritizing the risks identified and coming up with a mitigation plan to reduce the errors that matter for the success of the clinical trial. QRM is a collaborative effort between different stakeholders involved in the clinical trial and happens in parallel with protocol development. QRM, starts with protocol definition, spans through study conduct till database lock. Quality is an extremely important aspect of a clinical trial, especially given the fact that it impacts patient safety. It is important for trial sponsors to have a robust risk management mechanism in place to ensure that patient safety is not compromised. A proactive approach in identifying risks in a clinical trial would help the sponsors to put in place an effective risk mitigation plan and avoid fatalities, budget overruns, major adverse events, etc. attributable to lack of oversight.

Traditional QRM in clinical trials focused mainly on site visits, in-situ source data verification, source data review and audits conducted during and after a trial. However Clinical Trials Transformation Initiative (CTTI) encourages the use of Quality by Design (QbD) in 'Risk Based Monitoring' (RBM) of clinical trials. Quality by design has been successfully executed in the field of manufacturing, including pharmaceutical manufacturing, but has still not been fully translated in the clinical trial space as it is 'expert driven' rather than 'process driven'.  There are 4 elements to QbD, Plan, Do, Check and Act.



















Most pharmaceutical majors have established QRM processes in place to identify risks and come up with the mitigation plans. Our viewpoint is that they can take a more proactive approach and manage the risks in a better way to prevent/ reduce their occurrences. Pharmaceutical companies have huge repositories of past trials, both successful and unsuccessful ones and with the help of this vast repository, predictive statistical models based approach could be adopted to identify and quantify the risks early in the game. Based on the risk predicted for a study, the sponsor/ study team could come up with the appropriate mitigation plan which can be used in risk based monitoring. Predictive approaches have been used successfully in retail industry to enhance customer experience.

As a first step towards developing the model, Key Risk Indicators (KRIs) need to be identified. Some of the risk indicators could be protocol deviations, amendments to the protocol, quality issues, budget overrun issues, etc. The next step would be to identify the important study attributes that might impact the risk indicators. Examples of study attributes include, therapeutic area, study phase, statistical design, the number of subjects involved in a trial, etc. This would then be followed by model building, using appropriate statistical and machine learning algorithms, which would identify the patterns in the study attributes that lead to the behavior of risk parameters. The final step would be to use the models to predict the risk of a study. The predicted risk of a study can be categorized into different classes, namely, high, medium, low using color codes. This would help the sponsors in proactively coming up with a better risk mitigation plan for any trial in the future. This can be employed on an ongoing basis.


Infosys believes that statistics based predictive approach could very well be applied and adopted in clinical trials for better patient safety, quality of trials. Infosys, with its vast experience in ETL and data analytics space, would be an ideal partner to sponsors of clinical trials in aiding their proactive risk management process of clinical trials. Predictive analytics combined with RBM will have a very high potential to transform the way clinical trials are carried out.



November 16, 2015

Medical Camp - Data Integration for better Healthcare



It was March 2010 when RAHAT camp organized in Tribal district Mandla of MP treated 50000+patients for various ailments in 7 days. Camp was listed in Guinness book of world records. I was lucky to be part of such a mega camp as dentist, we witnessed various dental and oral diseases and a rear disease Noma(cancrum oris) whose reported cases in world are very few . In this camp huge amount of data was generated related to treatment modalities undertaken, medicines used and also disease pattern prevailing.

To my dismay this data was not converted into useful information which could be used in future to combat various endemic diseases, research and also I found lack of integration of various medical camp data which could be of immense help to healthcare industry.

I have noticed that to provide basic and also secondary healthcare, medical camps are organized by various organizations like WHO, UNESCO, Governments, and NGOS all round the world. Along with healthcare services these camps also generate data about diseases, medicine, procedure followed, patients and treatment options.

This data can be converted into information important for pharmaceutical industry, healthcare professional and govt. The data can be used as weapon to fight with various existing diseases, help develop new medicines and also identify emerging disease trends and identify new diseases.

Medical camp data is huge data which is unorganized and not integrated, making it difficult to use information for any good. This provides IT industry opportunity to develop systems that lead to proper utilization of all the data that is being generated and provide proper structural and functional data as required by the end user in order to draw complete benefits from these camps report.



Where is the Problem

Paper based reporting of camp is difficult to handle and information cannot be shared with other organizations when needed. Maintaining this paper based data is another problem.

Medical camps are organized in various location in the world, no single portal for camp registration, No standard way to report camp that is no template available, difficult data entry, data is not analyzed to draw useful conclusions, no integration of data from different medical camps, rural areas of various countries don't have basic facilities for camp to be reported, technical challenges in almost every step to make camp reporting feasible and organized.

Data from various medical camp is missed, this data can be used by various organizations according to the need.


Possible Solution:

  1. Convert paper based system to IT based.
  2. Common registration forum for medical camp treating more than 1000 patients.

  3. Standard template for camp reporting.

  4. Listing of all patients ,doctors and other healthcare provider participating in camp.

  5. Details of medicinal products to be used in camp and its manufacturer and supplier.

  6. Analysis tools incorporated in software.

  7. Use of software like MedSaaS for reporting and patient data.

  8. E protocol should be followed.(login information).

  9. Integration of data from all over world and also region wise integration.

                                                Text Box: Prototype for Integration of data*&auth=LCA%2080be12f4d61817c19a2833d1ac22c11cd4c269bd-ts%3D1439799554


All data from all over world should be collected and analyzed to find out

  1. Rare diseases incidence can be found and reported easily.

  2. New treatment which was effective can be reported for further research.

  3. Any issues with current treatment and also with medicine supplied can be found.

  4. Trends of emerging disease can be identified.

  5. Region specific disease can be identified(endemic).

  6. Helpful in identifying gap in medicines.

  7. Direction for pharmaceutical companies Research and Development.

  8. Adverse events with any drug will get captured.

  9. Can be helpful in taking preventive measures before any disease turns epidemic

Other things need to be addressed:

  • Patient confidentiality

  • Basic knowledge of computer and software to the camp organizers and team.

  • Regulation to make it mandatory for registration of camp.


This can be helpful to organizations like WHO, UNESCO, Pharmaceutical companies looking for new opportunities in Research and Development, and also to the governments of several countries.

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