Supply chain optimisation is the most prevalent theme in the process operations and management. A lot of work and studies are done on facility location and design, inventory and distribution planning, detailed scheduling. But, very little work has been done comparatively keeping the focus on the pharmaceutical sector.
At the initial supply chain design level, it's important to have an accurate capacity planning keeping in mind the anticipated demand based on the level of competitors' activity and on clinical trials. Efficient capacity utilisation plans and sound infrastructure investment would hold paramount importance as regulatory pressures increase would lead to a downfall in margins. At operation stage, it is difficult to get a responsive supply chain as most pharmaceutical products have a primary active ingredient (AI) production and secondary production. Both of the stages are elongated by the need for quality assurance activities at several points. The overall supply chain cycle time can be expected to be around 300 days. In this context debottlenecking and decoupling strategies along with inventory management are crucial for quick responses to changing market trends.
Operational issues in the pharmaceutical supply chain:
Although the process for each company would be different but each of them would be having an ERP system working in the following lines
• Demand management: For each geographical region, the demand for 3-4 month is predicted based on the historical data available, marketing intelligence and once the quantity is estimated then tenders for manufacturing is floated.
• Inventory management and distribution requirements planning: The demand ascertained are broken down and assigned to individual demand centre which will handle that portion of demand. The impact on finished goods inventory is assessed and if necessary, orders are placed on upstream secondary manufacturing sites.
• Secondary production planning and scheduling: the orders placed on the secondary sites are planned (typically using MRP-II type tools) and then scheduled in detail (typically using APS tools). The impact of production plans on active ingredient raw material stocks is evaluated and if necessary, orders for AI are placed on the upstream.
• Primary manufacturing campaign planning and AI inventory management: The demand of the secondary manufacturing is satisfied by careful inventory and production planning.
An interesting feature of this process is that the customer-facing end is effectively a “pull” process (driven by orders) but the primary manufacturing stage has long cycle times which make it difficult to ensure end-to-end responsiveness. This means the entire process is a mix of push and pull with the primary manufacturing being push driven by medium-term and long-term forecasts. Fairly large stocks of AI must be kept to ensure a good service levels and ensure smooth operation at the interface of these processes. The well-documented “bullwhip” or Forrester effect is often felt at the primary manufacturing site, which is unfortunate since this is the least responsive part of the supply chain as it normally operates in campaign mode. This makes it difficult to exploit short-term opportunities (e.g. shortages of supply of a competitor's product, tenders for national supplies, epidemics, etc.).
Another feature of this process is an outcome of its large scale and geographical span. This is the distributed nature of decision-making, which can lead to tensions and sub-optimal decisions. Different nodes are not really aware of upstream nodes' resource constraints, and orders may be filled in order of receipt, rather than on an economic basis. Of course, centralised planning would not be without its difficulties in this context.
In our experience, the following supply chain performance measures are typical of the industry:
• The stock levels in the whole chain (“pipeline stocks”) typically amount to 30–90% of annual demand in quantity, and there are usually 4–24 weeks' worth of finished good stocks.
• Stock turns (defined as annual sales/average stock) are typically between 1 and 8.
• Supplychaincycletimes(definedaselapsedtimebetween material entering as raw material and leaving as product) are often between 1000 and 8000 h.
• The value-added time (time when something happens to material as a percentage of chain cycle time) is of order 0.3–5%.
• Material efficiencies (the amounts of product produced per unit amount of total materials used) are 1–10%.
The relatively high levels of stock are required to buffer the slow supply chain against market dynamics.
2.4. Strategic and design issues in the pharmaceutical supply chain
The decisions to be taken at this level include:
• Pipeline and development management—this involves the selection of potential drugs to develop further, and the planning of the development activity.
• Process development—the investigation of manufacturing routes and the generation of manufacturing processes.
• Capacity planning and plant and supply chain network
• Plant design—the selection and sizing of the major equip-
ment and storage units.
Some of the key issues are:
• Uncertainty in the demands for existing drugs (due to competition, uncertainty in the ability to extend the pro- tected life through new formulations, etc.).
• Uncertainty in the pipeline of new drugs—in particular, which ones will be successful in trials, what sort of dosage and treatment regime will be optimal.
• Process development—this is a complex problem, driven by chemistry and yield optimisation. It often results in inefficient processes that are operated much more slowly than the intrinsic rates—giving rise to batch processes and long cycle times responsible for some of the problems seen at the primary production planning stage.
• Capacity planning—the long lead times to make capac- ity effective mean that decisions often need to be taken at times of high uncertainty. Waiting for the uncertainties to be resolved might delay the time to market by an unac- ceptable amount.
• Network design—often tax implications take precedence over logistics issues, these result in economic but poten- tially complicated supply chains.
• Plant design—this tends to be very traditional, with no real change in manufacturing technology for 50 years (the workhorse of the primary manufacturing site is the glass-lined stainless steel batch reactor). There are signif- icant opportunities for intensified, continuous processing.
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