7 Reasons Why Big Data Will Revolutionize The Pharma Industry

Today, the pharma sector is one of the biggest players in the healthcare industry. The government and drug regulating bodies are encouraging pharma companies when it comes to R&D. However, the first step in R&D is obtaining and managing the huge chunks of data. Simply storing tons of data and then fishing through it when something specific is needed is like looking for a needle in a haystack. 

The first step involved in big data management for pharma companies is integration of data. Better integration means better efficiency. There are several steps that a pharma company can take to manage big data better, so that maximum benefits and potentials can be extracted from it.

7 Reasons Why Big Data Will Revolutionize The Pharma Industry

1.   Internal and External Linkages
Do not treat the pharma R&D sector as a secretive venture. Pharma companies need to collaborate better between internal and external sources, so as to extend their knowledge and data systems, along with obtaining end to end integration that starts right from drug research, development, advertising and delivery. 

Improving internal collaboration requires better linking between different sections of clinical trials. This helps in gaining insights across the chain, including multiple drug opportunities, improvisations, etc. External collaboration is between the company and the stakeholders involved including patients, providers, academic research professionals, etc. External collaboration can help in several ways, like; academic research professionals can help share insights regarding the latest scientific breakthroughs in drug trials and drug effectiveness. 

A leading pharma company has taken the initiative wherein external researchers can submit their compounds for screening and then, the pharma company can decide whether it is a potential drug compound or not. In this manner, the intellectual property of the researcher remains intact while the pharma company gets a firsthand look at potential new drug compounds. Not to mention, collaborating with customers means gaining a new insight from a user’s perspective.

Improving internal and external collaboration is easier said than done, as this requires high end communications systems and governance. The company needs to judiciously decide which data can be provided to outsiders and which is to be held, so that gains and insights such as inputs from research professionals can be obtained while strategy and developments are not revealed to competitors.

2.   Integrating Data Obtained
There are three qualities that data must have at all times – timeliness, accuracy and integrity. Data that is stale and inaccurate is not only unreliable but also may end up ruining the entire chain of procedures in the R&D section. 

Integrating the data obtained at every stage of the value chain, right from discovery to market release after regulatory approval is extremely important. Effective integration allows for making an authoritative source of information, irrespective of the source from where the data has been collected – external, internal, proprietary or public. Data integrity also allows for easy accessibility of subsets of data as there are often smart algorithms included that link certain areas of data. An example of this would be linking between laboratory and clinical findings, which could create automatic reports regarding areas such as efficacy and safety of drugs.

Hence, to ensure that there is complete integration of data, one needs various tools such as, trusted sources of information to begin with, the ability to establish links between sections of the data, workflow management and secrecy of certain sections of data so that it is visible only to the select few that are allowed to have access to it. 

The reason why CRM comes so handy in this department is that if pharma companies decide to overhaul their entire data integration system at once, it will lead to logistical problems and very high costs among other problems. Hence, a two step approach makes more sense in such cases wherein first, all the data is prioritized to understand which areas (such as clinical research data) needs additional data storing capacity on a regular basis so that important data can be obtained immediately when needed. After this, attention is paid to other aspects of the data such as analytic, ownership areas and various expected costs, projections and timelines.

3.   Improve Clinical Trial Efficiency
Clinical trials form the major chunk of pharma R&D which is why using cutting edge technology in this area of pharma is paramount. Newer and smarter devices allow for easier data exchange and enable improvement in clinical trial design and outcomes, thus ensuring better efficiency. Drug safety features and other red flag raising areas in certain sections of the population will be far easier to identify once smart devices that highlight these facts are used.

Other improvements that will take place include:  Understanding areas which are being ignored while obtaining population data can be corrected by adapting to differences in site patient recruitment. This will help find out areas that are lagging behind and will help to explore newer and more successful sites with better patient populations

Integration and updating of medical records by use of electronic data could help not only keep track of the patient prognosis but could also become the primary source of clinical trial data. This will reduce the redundancy of having a separate information system, thus accelerating the trial rate and reducing the chances for error due to duplicate entries. This way, remote monitoring of patients could also improve management, responses and monitoring of issues arising during the trial.

Also, re-estimation of sample sizes could be done so that smaller populations of patients can be analyzed enabling smaller trials that cost less but offer higher accuracy and efficiency.

4.   Making Use of Smarter Devices
Remote monitoring of patients with the help of sensors and devices is a huge untapped opportunity for pharma companies. It helps in increasing patient adherence to prescriptions. The advances in instrumentation when it comes to bio-sensors and various smartphone apps have become a tool for sophisticated health assessment. Making use of these tools instead of gathering hoards of data is far more feasible. This data could be used for R&D, to understand drug impact, efficiency and dangers, devising a marketing strategy for future sales, etc. 

Mobile providers are also waking up to these options and are offering services like data feeds, analysis, tracking of patient prescriptions, etc. Thus, use of these devices along with infrequent face to face visits with the patient can decrease health care costs by shortening hospital stays and identifying health conditions and their prognosis earlier on.

5.   Don’t Fear but Embrace Technology
The key to successful pharma R&D is to make use of state of the art technology. Cutting edge tools include sophisticated techniques like systems biology and high-throughput data production equipment. This is basically technology that has the ability to produce a lot of data within a short time span. A good example of this is next generation sequencing with which within two years, the entire human genome can be sequenced. 

Basically, the huge treasure trove that is big data will help future innovation and will feed the drug development chain. Analytical skills and know-how need to be top notch as many steps in pharma R&D, right from cross matching the right and most effective patient sample groups with the clinical trial requirement, to bringing the drug to the market, will become more efficient.

Using advanced technologies will make personalized medicine and diagnostics a part of the drug development process itself, thereby reducing the cost of drug production for pharma companies. Whats more, newer and improved modifications can be introduced in the drug before it is released into the market.

6.   Improve Drug Safety
The responsibility of the pharma company does not end on releasing the drug in the market. In fact, this is where the real test starts because drug effectiveness and word of mouth publicity can make all the difference. However, drug safety is a major issue and smart pharma companies can take this facet and use it as a competitive advantage. 

Nowadays, pharma companies are using dynamic safety monitoring methods. These companies keep an eye on various platforms and have multiple sources from where they receive information about their drug, such as online forums, physician communities, electronic medical records, etc. Besides this, the general reputation that the drug holds in the market can be best estimated from forums and communities, where target customers discuss real time issues with the drug. Certain analytical methods, such as Bayesian analytical method can help identify any untoward side effects occurring in the drug from recorded data with high accuracy and speed.

The main reason why this is an important issue for pharma companies is because besides maintaining their brand name, early response to negative drug reactions from patients and doctors will also prevent patient backlash and disciplinary action and blacklisting by FDA. A single drug blacklisted by the FDA translates into losses that run into millions for pharma companies. 

Nowadays, the FDA is investing in evaluation of health records through the Sentinel Initiative, a legally mandated surveillance system that links data from multiple sources for accuracy and relevance. In this manner, the FDA has managed to access and connect data of more than 120 million patients in the U.S.A.

7.   Focus on Drug Effectiveness and Outcome

It is needless to say that today, one of the most important success factors for pharma
companies is real world drug outcomes.

Consumers and patients are slowly becoming more aware and are looking for value based pricing options. Pharma companies should accordingly gather and analyze data so that they can successfully pursue drugs that can show for such cost-benefit pressures, such as target drugs with a high success ratio when used for treatment of diseases wherein they fall under the first line of drugs indicated.

There are many ways by which pharma companies can manage big data without fretting over it. Many of the steps mentioned can be easily implemented if a proper CRM software is in place to begin with. However, enabling the company with a better skill set and the required technology does not come cheap, as big data managers are few and high in demand. But once a pharma company has decided that it will leave no stone unturned to dig into the lucrative business of big data, then there’s no saying how far it will leave its competitors behind.

Related Articles:
1. KOL Process Management Simplified!
2. 6 Ways CRM in Pharma Ensures Continual Growth
3. 7 Reasons Why Big Data Will Revolutionize The Pharma Industry