PHARMACEUTICALS product components in place as a responsive stock buffer for supply chain disruptions . Choosing the right supplier plays a key role in agility , particularly in assuring the quality of purchased materials . In addition to dependable quality of materials , the right supplier provides comprehensive documentation that meets regulatory compliance , plus additional and customised testing to help control the successful execution of the final manufactured product . Partnering with the right supplier is both costand time-saving in avoiding nonconformities , deviations , potential reputation damage and loss of customer confidence .
Application of AI & digital tools
There has been a significant increase in digitalisation investment in both the pharmaceutical and biopharmaceutical industries since the pandemic . Digital tools and processes provide a competitive advantage in agility and speed , increasing efficiency in operations , better data quality through virtual data access , improved R & D productivity , faster delivery of advanced therapeutics , easier compliance and less wasted product . Deloitte shared the findings of its 2021 survey of 150 biopharma leaders to better understand the industry ’ s approach to digital innovation in this environment of accelerated change . “ Biopharma is now at a digital innovation inflection point . Organisations face an important choice : either decelerate the pace of digital innovation or pursue what we call leapfrog digital innovation ,” it noted . Deloitte ’ s survey results suggest that specific digital technologies are already widely adopted and incorporated into biopharma operations . More than a third of survey respondents reported using more digital technologies in day-to- day operations , including the cloud ( 49 %), AI ( 38 %), data lakes ( 33 % and wearables ( 33 %) in day-today operations . 4 These and other technologies have enormous potential to help create a digital transformation in global drug manufacturing that can accelerate speed to innovation and commercialisation of new products that will benefit patients worldwide . Significant competitive advantage is already with drug manufacturers that have been early adopters , recognising that the future is digital . Now , the industry as a whole understands that it is an imperative to implement strategic plans for digital innovation to succeed in the new digital economy .
Risk management & mitigation
Risk management is often referred to as ‘ decision-making under uncertainty ’. Risk management planning seeks to improve decisionmaking in identifying and controlling
Figure 2 - Digital innovation in the lab
Digital innovations
Al-driven drug discovery ( Al )
Automated lob processes ( robotics and lo T )
Virtual data assistances ( ARIVR , A /)
Interoperable data ecosystems (/ oT )
Seamless data shoring and access ( cloud )
Description
Al applied to knowledge graphs automated target identification and validation , and reduces time spent on screening of extensive molecular libraries to identify lead molecules . Al-based computational chemistry toolkits enable discovery scientists to explore novel spaces and broaden the pool of potential structures to consider as drug candidates , increasing development pipeline size and diversity .
Physical and digital robots automate lob processes such as sample preparation , pipetting and standard analytical testing , managing these activities with high precision and repeatability , reducing manual workloads .
Digital assistances with AR / VR , NLP ( natural language processing ) and computer vision facilitate hands-free work by displaying steps of a lob procedure and notes from previous experiments while automatically recording all video and audio observations .
Through lo T , research platforms and smart instruments can automatically clean , store and upload data to cloud platforms to create an interoperable lab ecosystem . This will ensure connectivity , access and availability of data and insights from discovery experiments when needed .
Through the creation of seamless and dynamic workflows via cloud data storage , scientists across organizations and geographies can effortlessly share data collected during experiments ( such as audio recordings and research notes ) and work together to analyse data and strategize follow-up experiments .
Source - Deloitte
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