3 Pits that a Life Sciences Company Must Avoid to Drive a Successful Crowdsourcing Business Model

See on Scoop.ithealthcare technology

Crowd sourcing business models like PatientsLikeMe, 23 and Me and innovation reward models like Innocentive have served as guiding beacons for pharmaceutical corporations looking to access rich data across patient populations. A fair share of companies engage in data licensing strategies to monetize the crowd sourced database. Some like Innocentive offer monetary rewards for competitive solutions. While certain others consider crowdsourcing as an idea pool that is gratis.

However, unlike a whole bunch of other industries where crowdsourcing does not have grave implications for society, the diffusion of crowdsourcing and creating a sustainable business model is faced with certain critical issues.

Issues , if you from the vantage of a pharmaceutical or biotechnology company, scientist or patient ignored could lead your crowdsourced business go bankrupt :


Build a Trustworthy Set of References: While boiling the ocean to save the world is a great philanthropic act, it is important for pharma biotechnology companies to ensure that data and solution contributions are at their authentic best. Similar to a host of Open initiatives, specifically those that are focused on knowledge building, the lack of a respectable source could potentially wreck an ambitious drug development program within the organization.


Whose Invention is it Anyway? The biggest dread of all pharmabiologists is the allegiance to inventions. The greatest challenge for your pharmaceutical organization is to ensure the demarcations of Intellectual Property Ownership. With the transition of the life sciences industry into a genetics driven enterprise, the spectre of “Informed Consent” become more important than ever. Hence drafting a strong legal protection against disruptions to your Crowd sourcing business is perhaps more valuable than filing a NME approval.


Separate the Music from the Noise: Large data does not necessarily mean better insight. For instance, given the alarming rate at which the NCBI database is growing, there is little chance that all the data available on cancer genetics and epigenetics is going to lead to much innovation within the next 5 years. Contradictory data points have emerged as a significant challenge for life sciences organizations. This in turn has lead to a massive churn of effort and tools being developed to validate the noise. Unfortunately, the crowd sourcing effort only compounds this problem. The influx of a wide array of ideas centralized towards a specific disease requires that pharma biotechnology organizations invest in a reference repository of past experimentations within their portfolio, to ensure that only the most relevant data is considered.


The key challenges of adopting crowdsourcing in the life sciences industry are unique but not insurmountable. Informed investment in data management and business model transformation, could transform crowdsourcing as a potent source of sustaining and disruptive innovation in the life sciences industry. More on how the life sciences industry could surmount the challenges in the next post.

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