R&D returns fall to lowest level in nine years

Pro­ject­ed returns on invest­ment in research and devel­op­ment (R&D) for the top 12 bio­phar­ma­ceu­ti­cal com­pa­nies have fall­en to 1.9 per cent, accord­ing to a study by Deloitte’s Cen­tre for Health Solu­tions lever­ag­ing rev­enue fore­casts and indus­try bench­marks gen­er­at­ed by Glob­al­Da­ta, a lead­ing data and ana­lyt­ics company.

The study enti­tled, ‘Unlock­ing R&D pro­duc­tiv­i­ty: Mea­sur­ing the return from phar­ma­ceu­ti­cal inno­va­tion 2018’ pub­lished by Deloitte, reveals that returns are down 1.8 per­cent­age points from 3.7 per cent in 2017, and fore­cast aver­age peak sales are at $408 mil­lion (£302m), mak­ing 2018 the low­est lev­el since Deloitte’s first R&D report in 2010. In the rapid­ly chang­ing bio­phar­ma land­scape, R&D returns have dropped by 8.2 per­cent­age points from 10.1 per cent in 2010.

The increase in aver­age cost of devel­op­ment of bio­phar­ma­ceu­ti­cal drugs is a dri­ver of this declin­ing return. Aver­age costs of devel­op­ment before reg­u­la­to­ry approval for com­mer­cial­iza­tion have increased in six out of the last eight years, with the aver­age cost now at $2,180 mil­lion (£1,616m), almost dou­ble the cost back in 2010 of $1,188 mil­lion (£880m).

The study also con­firms that a sys­temic approach to pro­duc­tiv­i­ty improve­ment, dri­ven by inno­v­a­tive stream­lin­ing approach­es, is need­ed to lessen devel­op­ment costs and time­line, ulti­mate­ly increas­ing R&D returns. Com­pa­nies need to act now and embrace new ways of work­ing, embed new tech­nolo­gies, such as Arti­fi­cial Intel­li­gence (AI) and Robot­ic Process Automa­tion (RPA), and seek out tal­ent with the right skill sets to opti­mize their return on invest­ment in phar­ma­ceu­ti­cal innovation.

“The good news is that advances in these tech­nolo­gies are already start­ing to have an impact in R&D. Com­pa­nies will increas­ing­ly use AI, in par­tic­u­lar machine learn­ing algo­rithms, to reduce R&D cycle time, costs and ulti­mate­ly build a strong and sus­tain­able drug pipeline. We will also con­tin­ue to see use of AI extend beyond drug dis­cov­ery and lead opti­miza­tion to play­ing an impor­tant role in clin­i­cal tri­als – not only for ana­lyz­ing the large amounts of data being gen­er­at­ed from clin­i­cal stud­ies but also for tri­al recruit­ment and management.”

Bon­nie Bain, PhD, Glob­al Head of Phar­ma at GlobalData

In addi­tion to the 12 orig­i­nal cohort com­pa­nies, since 2015 four small­er and more spe­cial­ized bio­phar­ma com­pa­nies have been includ­ed as an exten­sion cohort of the R&D study.

Con­sis­tent with the orig­i­nal cohort, these com­pa­nies also saw returns decline to 9.3 per cent in 2018, from 12.5 per cent in 2017. How­ev­er, this drop was main­ly dri­ven by the increased costs of com­mer­cial­iza­tion of five high val­ue drugs from the four com­pa­nies. In line with obser­va­tions from pre­vi­ous years, these small­er firms con­tin­ue to out­per­form their peers, find­ing suc­cess in iden­ti­fy­ing high val­ue prod­ucts with sig­nif­i­cant unmet med­ical needs. These prod­ucts have added $70 bil­lion (£52bn) of pro­ject­ed life­time sales to the com­mer­cial port­fo­lio across the four com­pa­nies. The exten­sion cohort has also increased the fore­cast peak sales per asset from $952 mil­lion in 2013 to $1,165 mil­lion in 2018.

“In the past decades, we’ve wit­nessed a con­sis­tent and rapid decline in R&D return in part dri­ven by a shift towards the devel­op­ment of more elab­o­rat­ed bio­log­i­cal solu­tions, for increas­ing­ly com­plex dis­eases, includ­ing ones pre­vi­ous­ly con­sid­ered as intractable, and in pro­gres­sive­ly more com­pli­cat­ed land­scapes. Over time, increased built exper­tise in care­ful­ly pri­or­i­tized ther­a­peu­tic areas, com­ple­ment­ed with machine learn­ing, may be key to off­set some of the risks and costs of bring­ing new ther­a­pies to market.”

Cyn­thia Brisac, PhD, Sr Strat­e­gy Con­sul­tant at GlobalData