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It is a well known fact that clinical trials nowadays are just getting bigger, more complex and expanding to the different parts of the globe. Also the timelines involved are reducing at a much rapid rate. In the era of outsourcing, large number of trials seems to come as a astonishment, both to the client and to the vendor, with whom they partner in the packaging and distribution process. Each department has a distinct common goal in terms of reaching the effective trial start date and ensuring that each patient and site is provided with the medication of the right dose at the right time. Clinical trial supplies more usually occupy the critical path bottleneck in terms of availability, therefore affecting cycle times for getting new drugs to market for marketing. There are quite a few number of best practices and tools that can be used for the trial to ensure that the clinical supply chain is managed more effectively and operates more efficiently.
Time and cost-efficient clinical trials require effective management of the supply chain. The key is visibility throughout the chain, from raw materials through final delivery. Getting clinical trial supplies produced, labeled, packaged, and delivered on time and to the correct sites is challenging. Doing so in a global, multilingual, regulated business environment requires the right technology. The technology should provide the automated, integrated control of the clinical trial supply chain. It should reduce clinical trial supply cycle time to almost half and can also optimize drug inventory leading to inventory reductions of 25%. Clinical trial supply chain can also be enhanced by enabling effective collaboration between and across research, manufacturing, contract organizations, regulators, and clinical sites. This high level of collaboration eliminates waste and late deliveries that are characteristic of clinical trials. Consolidating and integrating data across systems and relationships can help manage the challenges associated with supplying investigational and comparator drugs for clinical trials. Ensuring the efficiency and validity of clinical trials requires that several factors come together, not the least of which is the investigational material. And the supply chain underlying a clinical trial is a complex entity, with product passing through numerous hands before reaching the clinic and, ultimately, the patient.
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Clinical trial supply managers face main challenges in tracking drugs through this journey, including figuring out ways to manage supply data. For example, to ensure that all the required tracking data is captured, trials are installed with information systems at every point along the supply chain, such as forecasting, inventory management, labelling, and distribution. But these information systems are not always interoperable; there are no industry standards for clinical trial supply chain management similar to Clinical Data Interchange Standards Consortium (CDISC) standards which are widely used for Electronic Data Capture (EDC). Thus, to process such information, sponsors generally have to store and give a proprietary code that would allow these systems to exchange data. Moreover, it is not necessary that all of the information systems are automated or electronic. Most trials still rely on manually entered data in excel sheets or even paper-based systems. These methods can be a real problem during the audits or FDA inspections, as they force trial sponsors which have the final responsibility for all data gathered from every function of a trial, including supply management to spend significant time and resources to reconcile the data.
Also the practice of outsourcing itself acts as a big challenge. According to the recent survey in Contract Pharma ( Roth G., 2008, 4th Annual Outsourcing Survey, Contract Pharma, Vol. 10. Issue 4.) indicated that out of 175 biotech and pharma companies, 48 per cent used more than five outsourcing vendors in their clinical study. The road that a drug take through the number of vendors differ from study to study. And since, the study sponsor is finally responsible for all relevant information generated by the trial, including data from outsourcing vendors.
Moreover, the study design is also mutating, with adaptive trials becoming more common. The dose of an investigational drug and the number of trial subjects, usually change drastically, which can hugely impact forecasting and management of the supply chain. Also, trials nowadays conducted internationally, reaching out to patients in multiple countries is also a big challenge so as to achieve greater control. Thus, supply chain model must account for the regulations of each participating country, including packaging and labeling rules, and make sure that an appropriate amount of investigational drug and standard drug reaches the patients in each country.
These challenges have increased the complexity of clinical trials. Examples of this increased complexity include the expanding number of clinical trials in which new drug candidates are tested against active controls (approved, marketed drugs); clinical trial designs incorporating more arms (patient sub-groups); adaptive trials; and the growing number of sites per study.
These challenges can also be specific at each stage of supply chain such as at packaging, forecasting logistic etc. for instance, at packaging level large multi-arm studies greatly increase the number of packaging configurations needed to conduct a trial. A study with at least one active control, one placebo, and a development candidate can easily have six or more packaging configurations, depending on the protocol. If the study is being conducted in multiple countries, labeling the packages to incorporate multiple languages is an additional challenge.
Moreover, these large multi-country studies make clinical supply forecasting very difficult. For example, estimating how many kits will be required in each country means being able to forecast enrollment rates with some accuracy, which is extremely difficult. Adaptive trials further complicate the problem. Also shipping clinical supplies to multiple countries raises problems such as transportation and storage under good manufacturing practice (GMP) conditions. Because of the growing number of biologics, maintenance of temperature conditions across the supply chain, i.e., cold chain management has also become a major concern.
The growing complexity of clinical trials and the clinical supply chain has now opened up an "arms race" in the clinical supply chain industry because participants are competing to offer the most sophisticated capabilities. For instance, clinical packagers are investing millions in information systems that can track individual packages from the warehouse shelf through every step in the supply chain, all the way to the clinic or physician's office where the patient receives his drug supply.
In addition, supply chain complexity has boosted the importance of a range of specialty providers and services across the supply chain. For example, Comparator sourcing companies that specialize in procuring drugs used as active controls in clinical trials. This is an intricate undertaking because bio/pharmaceutical companies often require large quantities of a drug from a single manufacturing lot when conducting active control trials. Also Courier companies that specialize in shipping materials to clinical sites and depots around the world. This is a booming business, with high double-digit growth rates. Lastly, Clinical supply depots that provide GMP-compliant storage for packaged clinical supplies. Depots enable bio/pharmaceutical companies to ship multiple kits to a country at one time, reducing shipping and customs-clearing costs, and ensuring timely delivery to patients. Once an ancillary service offered by a few contract research organizations (CROs), clinical supply depots now are a critical link in the supply chain.
Approaches for better clinical supply chain management:-
Once a trial starts and recruitment gets into gear, supply stock levels often start to deplete at a different rate than expected. Add to this the needs of expiry date management and soon supplies can start to dwindle. It is essential that stock level data is monitored throughout the entire supply chain, but due to multiple parties and systems involved this is not a straightforward process.
Some large Sponsor companies have inventory and management systems capable of monitoring various portions of the supply chain. However, when the decision has been made to outsource portions of the supply chain, Sponsor companies suddenly find a gaping hole in any materials management systems. Also in most instances, once shipped globally, supplies can disappear totally from the Sponsor's radar, therefore creating a reliance on unconnected reports from other systems (mostly 3rd party), which require manual manipulation of data to forecast future supply needs and manufacturing requirements.
Another inherent problem can be that various inventory reports and stock levels are available, but the supply chain is not covered for each required component and does not look back in totality to bulk material and component availability. It is useful to note that as kit inventory is monitored by whatever means selected by the Clinical Managers, plans must be included to make the information available to each participant in the supply chain. This means that outsourcing partners need to be involved in relevant data exchanges that may affect the availability of additional supplies, and that this involvement occurs in a timely fashion. Joint meetings involving Sponsor companies and associated vendors prior to study commencement are invaluable. Such meetings can present a platform to examine interface exchanges and possible alternative approaches to the study design. Also, it is possible to have one vendor responsible for multiple areas of the supply chain, therefore enhancing control and reducing management concerns. A variety of different approaches are available for management of the supply chain when the study goes live, but the Trial Supply Manager must link the inventory data back into the complete chain. Examples of inventory management include: -
The manual approach:- Many Sponsor companies employ a manual approach to the supply chain. Generally this will mean pre-defining set amounts to ship to each site on activation and then another set amount for further supplies. This can result in reduced visibility of the inventory and provide difficulties if sites take on a different level of activity than predicted. Supplies are usually manufactured/ packaged with at least of 100% overage, therefore adding to the trial cost and lead times for production. Study monitors can provide inventory verification but this approach can lead to a fragmented approach if multiple supply campaigns are required.
Interactive Voice Response Systems (IVRS) :- Traditionally both IVR, and similar web based systems have been the scope of large Phase III trials, with complex dosing and inventory requirements. However the quality of reporting tools available and management of randomisation has encouraged increased use within the industry. An IVRS provides full visibility of released finished patient kits held in Sponsor, or third party depots, and also at the study sites. During study set up, it is usually decided to supply sites either by using defined stock levels that are resupplied based on various set trigger points, or by a just-in time delivery (for each patient visit) depending on the best fit for the study. Ultimately, this can assist the clinical trial supply chain in not only presenting alerts for low stock levels at sites, but also in country or central depots such as a contract packager/distributor. The ability to manage the supply chain at site, country depot and central depot allows the trial medication to be managed more effectively, and can assist in the overall supply chain. Again, lead times for all components (such as bulk drug) and production of supplied kits, means that careful monitoring of this interface is required. It has already been possible by agreeing common data set protocols to permit data interchange between IVR and distributor systems to facilitate electronic ordering of patient supplies. Although not full integration, it does at least serve to enhance reporting, visibility and ordering efficiency, especially when integrated with bar coding of the clinical supplies. By utilising a vendor with both distribution and IVR expertise, the trial supply can be integrated with input on streamlining trial set up and management of drug inventory.
Forecasting Programs:- Programs are available that can simulate different trial supply scenarios and model the affect of using differing variables in terms of patient recruitment levels, the quantity of site shipments and multiple site supply strategies. In combination with IVR or in isolation, these can be effectively used upfront to help decide on actual site supply strategies. Forecasting can also be used to estimate how long quantities of supplies will last for. This can be particularly useful when the study has commenced and forecasts need to be made covering the entire supply chain for resupply of study kits.
Electronic Data Capture Systems:- Although primarily for quality data collection, certain data sets within EDC systems can be used by distributors to predict an efficient justin time drug supply, again helping effective monitoring of inventory and reduction in waste drug. By using patient enrolment information and also establishing specific dispensing visit timetables, inventory can be managed between a distributor and EDC system. In our experience, this approach can work well for trials with simple dispensation rules and minimum dosing scenarios.
However, implementation of such solutions is not without its own challenges. For instance, as noted above, the industry has not agreed upon standards for formatting, storing, and exchanging supply chain data. For now, most organizations overcome this challenge by creating proprietary transformation and exchange tools that bridge disparate systems. This is not, however, an ideal solution, as the process for developing, validating, deploying, and maintaining such bridge tools is onerous and time consuming. Such solutions also do not provide adequate flexibility to accommodate various system upgrades or easy replacement of one or more of the component systems in the supply chain. For this reason alone, a concerted industry-wide effort towards development of standards would bring new efficiency to supply chain management, just as it has for data capture and trial management.
If a combination data mart-business intelligence system were to be used in GMP-related decision making or study reporting, it would have to undergo system verification. This is a time-consuming process, but one that would give assurance of the reliability and fidelity of the storage solution and accuracy of the analyses generated using the business intelligence component-an important consideration when looking forward to regulatory submission.
Data contained within a data mart is only useful if it can be queried and accessed in ways that fit an organization's reporting and analysis needs. Thus, systems built on this combined model must be constructed with intuitive and flexible reporting in mind. The data mart must be understandable in order to allow the inclusion of ad hoc reporting. KPIs, which can be of great help in pointing out areas for improvement that would increase overall organisational efficiency, can be difficult to extract from supply chain and inventory data unless the system is built with the foresight to allow for measurement of the proper metrics. Information systems have evolved such that decision making in near real-time is possible. But how real-time will a data mart system be? Or need to be? Because of the limited availability of industry experience with such solutions, the first question is difficult to answer. The second can only be addressed by a thorough examination of trial protocol's information needs, with particular consideration of decision timeframes and the temporal resolution needed to support them.
Several companies involved in outsourcing have attempted successfully the process of data integration on specific parts of the supply chain. However the main issue remains that with so many differing in-house systems and services provided by third parties that solutions tend to be point to point. As a result Sponsor companies that use a suite of tools to manage the clinical trial supply chain face multiple areas of data integration. Each of these requires programming, testing and validation for each source in the chain. Likewise, the vendors also will have this problem for each Sponsor Company they are involved with. However, this may not be the case in the future. Organisations such as CDISC (www.cdisc.org) are working to establish guidelines for data transfer standards, which could provide a platform for future integrations. Also file transfer protocols, such as XML, offer enhanced possibilities for data transfer. Data portals that allow multiple sources to "speak" using an integration layer present an opportunity for automated data sharing between companies, therefore feeding data from site, depot and the manufacturing facility to allow tighter supply chain integration.
Sponsors can help the clinical trial supply departments both of their own company and in their outsourcing partners, by planning before hand and giving some direction to the drug development plans. This will facilitate the management of demand forecasting and capacity, and also identififying potential hurdles before hand. Further use of information systems to control and manage all the points of the clinical supply chain means that data integration needs will escalate within the industry. Organizations will desire and work hard to focus not only on operational expertise, but also on the ability to integrate into set data standards that allow them to take their place in an integrated supply chain.
This kind of automation and standards-driven paradigm of trial supply management will bring the same efficiency and integration now being seen in trial data collection. The development and adoption of information system models like data mart-business intelligence will accelerate the evolution of this paradigm. At the same time, it will offer significant advantages in trial efficiency now, enabling companies to more rapidly enroll and execute clinical trials and reduce the time to market for new innovative products.