IN PARTNERSHIP


Finding hidden treasure: How biotech and pharma can accelerate study timelines in Phase I and Phase II using trends hidden in the data they already have


In the crrent maret, efficiency is a vital advantage. etting the most ot of yor cash rnway is an idea everyone can get behind. o why do iotechs arond the world still have to wait wees or even months after their last patients last visit to see their data and mae a decision


S


tarting from the beginning of the clinic, every drug goes through a Phase 1, most of which are dose escalation


trials. Currently, Pharma and Biotechs run the entirety of their trial with the different dose levels, wait for the data to get put together at the end, then make a decision. Often there are entire cohorts dosed too high or too low, and at an average $100,000 a patient, the impact on the bottom line is signicant.


ow do companies avoid this potential money and time sin y analysing datapointby datapoint, patientbypatient, in real time as the dose escalation is ongoing. hen this is being done, companies will have mltiple advantages. irst, they are able to avoid the wait time following the completion of a cohort and instead mae their dosing decision as hidden patterns are revealed in the cohort. et, becase they are doing this, companies are able to add to responding cohorts midstdy, saving time and money. There are proven systems and services that can facilitate this that have been arond for over a decade and have been sed for nearly a doen A approvals, sch as The ingle


34 | Outsourcing In Clinical Trials


Interface from revail Infoors. e spoe to ac oriet, the  of revail Infoors, and he waled s throgh a recent case where $ million and  months were saved across a program sing this approach in a dose escalation hase II, which then conted as a pivotal


“A North American pharmaceutical


company focused on autoimmune disease was attempting to succeed where large pharmaceutical companies had failed. The company had a promising therapy in a challenging therapeutic indication – one which had already seen more than 30 drugs tried and failed by other sponsors. The customer had begun a Phase II dose-


escalation study which required detailed and frequent reporting to a DSMB to get permission to dose escalate. However, the company was relying on highly experienced researchers to do this manually, which was extremely time- consuming, risked data quality, and was taking a talented research team away from higher- value work on the study such as assessing progress towards study endpoints. Recognising that gathering quality data more quickly – in a manner lending itself to faster


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