Tapping into the ‘$100-billion digital opportunity’ in pharma

A struc­tured approach to deploy the dri­ving force of data can help com­pa­nies ener­gise their busi­ness and cre­ate a land­scape where inno­va­tions such as arti­fi­cial intel­li­gence (AI) and pre­dic­tive ana­lyt­ics move clos­er.

Research has shown that fail­ures to realise dig­i­tal inno­va­tion cost the indus­try €16.9 bil­lion¹ a year, while labour-inten­sive pro­ce­dures cor­rode the morale of sci­en­tists and com­pro­mise their abil­i­ty to dis­cov­er and devel­op new ther­a­pies.

“Get­ting your dig­i­tal approach wrong has a mas­sive impact on a company’s bot­tom line,” says Dr Haydn Boehm, head of com­mer­cial mar­ket­ing at Con­nect­ed Lab, a part of Mer­ck, which is ded­i­cat­ed to unlock­ing the poten­tial of data across the entire phar­ma indus­try val­ue chain.

“Sci­en­tists are spend­ing up to 60 per cent of their time on data entry and cleans­ing tasks when they should be con­cen­trat­ing on the sci­ence. But there are easy steps we can take to lib­er­ate their time and deliv­er val­ue-based change, rather than view­ing AI as some­thing that will mag­i­cal­ly trans­form every­thing.”

Ana­lysts at McK­in­sey & Com­pa­ny have char­ac­terised dig­i­tal in research and devel­op­ment as the “$100-bil­lion oppor­tu­ni­ty”² with its poten­tial to rewrite the cur­rent script of sin­gle drug devel­op­ment cost­ing $2.6 bil­lion³, while return on invest­ment con­tin­ues to fall.

Boehm answers ques­tions about the cru­cial steps need­ed to har­ness data to dri­ve improve­ments across every aspect of phar­ma, from inven­to­ry to secu­ri­ty and reg­u­la­tion to staff reten­tion.

Why do pharma companies need to examine how they view and use digital?

Every­one views AI as a panacea, but the real val­ue is in drilling down into how your data can be used in your com­pa­ny. There could be many easy oppor­tu­ni­ties to lever­age dig­i­tal tech­nolo­gies and ser­vices to unlock the full poten­tial of your busi­ness and increase process effi­cien­cies. But if your data is not cap­tured effi­cient­ly, or is not read­i­ly acces­si­ble to the peo­ple who need it, you are nev­er going to be able to cre­ate data-dri­ven busi­ness mod­els.

What are the first steps to making data work for a company?

It is impor­tant to recog­nise process­es that involve a lot of human labour and motion waste, or unnec­es­sary move­ments, which can be a sig­nif­i­cant ele­ment of how your data is cap­tured, stored and used. Address­ing this lays the foun­da­tion for util­is­ing more AI and get­ting mea­sur­able ben­e­fits from it. Some com­pa­nies are hir­ing sci­en­tists sim­ply to cleanse data but, if you opti­mise data cap­ture and input, you can employ those sci­en­tists to do what they are trained for and what they want to do.

What is the potential from enhanced digital practice?

It can have a trans­for­ma­tive influ­ence where it mat­ters, reduc­ing costs, improv­ing pro­duc­tiv­i­ty, increas­ing capac­i­ty and speed of deliv­ery, which has a huge impact on cus­tomer sat­is­fac­tion. This enhances brand rep­u­ta­tion and com­pa­ny equi­ty. It also allows com­pa­nies to opti­mise resources and the integri­ty of data, which is a fun­da­men­tal spring­board to greater use of AI across the organ­i­sa­tion. The chal­lenge is to analyse your approach to data and cal­cu­late where dig­i­tal will be most effec­tive.

Why is it important to have good data?

If your data is clean and trust­wor­thy, you can achieve so much more sci­en­tif­i­cal­ly and struc­tural­ly across the com­pa­ny. It is also vital for secu­ri­ty and com­pli­ance, which are very impor­tant fac­tors. Hav­ing data that can­not be shared with exter­nal part­ners, or even inter­nal­ly, ham­pers devel­op­ment, and pur­su­ing the indus­try-stan­dard prac­tice of pro­duc­ing tri­al and safe­ty data on PDFs can cause issues with reg­u­la­to­ry author­i­ties. The US Food and Drug Admin­is­tra­tion and Euro­pean Med­i­cines Agency are mov­ing away from paper reports and into dig­i­tal, so com­pa­nies need to syn­chro­nise with their require­ments or run the risk of cen­sure. Hav­ing data that is not com­pli­ant with FAIR (find­abil­i­ty, acces­si­bil­i­ty, inter­op­er­abil­i­ty and reusabil­i­ty) prin­ci­ples is anoth­er issue that hits the bot­tom line and a PwC report esti­mat­ed it costs the Euro­pean econ­o­my €10.2 bil­lion a year in delays and lost oppor­tu­ni­ties.

Can it improve drug development?

This is exact­ly what it does. Enhanc­ing and har­mon­is­ing process­es and reduc­ing motion waste cre­ates more time and space to inno­vate and pur­sue dis­cov­ery. The tar­get­ed use of dig­i­tal tech­nol­o­gy can help deliv­er bet­ter pre­dic­tors of what would be a suc­cess­ful mol­e­cule. Bet­ter data gov­er­nance means you can col­lab­o­rate on more pro­duc­tive terms and also inter­ro­gate his­tor­i­cal data to gen­er­ate new leads and speed up dis­cov­ery process­es. There are so many oppor­tu­ni­ties going to waste because the data is not clean or reusable, or it is dif­fi­cult to locate and share. At the core of this is the sci­en­tist and anchor­ing them down with data-cleans­ing tasks and mul­ti­ple tran­scrip­tions of reports is counter-pro­duc­tive. They need to be spend­ing 100 per cent of their time prob­lem-solv­ing and dri­ving sci­en­tif­ic pro­grammes for­ward. They should not be shack­led when dig­i­tal resource man­age­ment can free them to do their job.

What are the downsides of not addressing data?

The impact of lost oppor­tu­ni­ties is immense and it means com­pa­nies lose out to com­peti­tors on many fronts. Con­tracts are lost, con­fi­dence is affect­ed, staff reten­tion becomes an issue and, ulti­mate­ly, brand rep­u­ta­tion suf­fers. All these neg­a­tive­ly impact the bal­ance sheet. It is key to look at areas where util­is­ing dig­i­tal tech­nol­o­gy can make a dif­fer­ence, such as pro­duc­ing reports or respond­ing to reg­u­la­to­ry affairs, which can be a mas­sive human bur­den, or hav­ing sci­en­tists spend­ing 45–60 per cent of their time cleans­ing data.

¹ Cost of not hav­ing FAIR research data, PwC EU Ser­vices March – 2018

² Dig­i­tal in R&D: The $100 bil­lion oppor­tu­ni­ty, McK­in­sey Ana­lyt­ics 2017

³ Tufts Cen­ter for the Study of Drug Devel­op­ment, Brief­ing: Cost of Devel­op­ing a New Drug, Novem­ber 18, 2014

Pro­mot­ed by Mer­ck