In todays situation where a lot of attention is put on the whereabouts of the pharmaceutical industry, especially focusing on productivity, pricing policies, time lines, and competition, there is an increased need for a critical revision of work practices in the business. The prevailing prioritization of time-to-market is now more and more shifting over to also put quality, risk management, and effectiveness/efficiency in the limelight. Resources in terms of people and money will continue to be constrained and, therefore, best collaborative principles have to be adopted between different parts of the organization. Only by operating this way will we maximize the output. One of the most important key performance indicators in pharma R is the number of newly appointed candidate drugs (CDs). However, it is not only a matter of counting numbers but, more so, to nominate compounds with the best properties and likelihood to survive. In that vein the demands on Process R have gone up considerably over recent years and there is now a pronounced need to make forecasts on cost of goods for the API (active pharmaceutical ingredient), scalability issues, IP matters, route design etc. On top of this, there is as always an expectation that the supply of material needed to conduct the various studies is timely, fully reliable, and flexible, even if volumes and delivery dates fluctuate widely. To successfully be able to cope with this challenging and sometimes stressful situation a back-integration into earlier parts of Drug Discovery is a must and, hence, connecting to new projects will have to be initiated already during the LO-stage (lead optimization). The consequences of this and its further implications will constitute the core part of the paper.