The drug development process is a topic you wouldn’t overhear being talked about too often unless you work in the medical field. Most people would have no idea, and a few might throw around important keywords like clinical trials and drug research.
Regardless, drug development is an essential process in the medical field. It stands to reason that it must be done as efficiently as possible to quickly create and distribute helpful medicine to eradicate people’s suffering.
While there are a lot of steps involved in the drug development process, the critical phase where most optimisation can be applied is the clinical research stage. To know more about how people can make it and some of the other stages efficient, resulting in a more optimised drug development process, keep on reading.
- Employing CDISC Standards
Clinical Data Interchange Standards Consortium (CDISC) is a non-profit organisation founded to establish data standards for clinical trials. It’s been around for two decades now. The CDISC and its role in clinical research are crucial, as it helps researchers standardise their methods of acquiring, exchanging, submitting and archiving data for clinical research and trials.
However, not all regulatory bodies worldwide require trials and research to adhere to CDISC standards. Currently, only the United State’s FDA and the Japanese Pharmaceuticals and Medical Devices Agency (PMDA) require CDISC standards to be followed by organisations planning to submit their findings.
Of course, there are other standards as well. You have SNOMED, MedDRA, LOINC, ISO, IHE, HL7, and DICOM. Unfortunately, having a lot of them can make things confusing. The reason people need standards is to make things uniform. Using different ones can only bog things down; it’ll be like using metric and imperial systems simultaneously.
Nonetheless, it doesn’t mean that you should force yourself to follow CDISC standards. The main point here is only to follow one, so discuss it with your organisation on which of them you will adhere to.
- Big Data
Optimistically, big data can help clinical trials. After all, the results of these trials and research greatly depend on the quality and quantity of data an organisation can collect. Big data may be collected from participants or third-party companies to help with discovery and development and preclinical and clinical research.
Currently, big data has a lot of proponents in the medical field. However, some smaller organisations may not be able to utilise it yet as there’s a cost barrier. For example, hardware and software costs alone (acquiring third-party services, getting wearables, providing smartphones or apps) may become a setback for a trial’s budget. Nonetheless, it’s projected that these costs will become lower over time.
- Outsourcing
While outsourcing has been stigmatised for the past few years, it can help optimise your drug development in terms of cost. There are many countries and locations in the world where labour is inexpensive.
Aside from that, some parts of the world are rich with more unadulterated participants—people with drug-free lifestyles and bodies and low chances of having a history of substance misuse. Together with this, most of them are often more willing to become participants in trials. Having more people in the research can significantly expedite the start of the trials, as finding candidates is often a very time-consuming process in drug development.
Of course, outsourcing still has inherent risks. Incompetency can be one, and ethical concerns are another. It doesn’t help that the latter can quickly become a huge issue if not dealt with properly.
- Be Constantly Updated With Regulatory Agencies
Once clinical research is done, the next stage is often a review from the regulatory agency you’re under. Unfortunately, these agencies can decide if your new drugs will be approved. That’s not the only concern you may have with them, as it’s common for trials to be crushed by many regulatory burdens.
These burdens often force an organisation to bend over backwards just to satisfy the requirements imposed on them. Thankfully, some powerful regulatory agencies sometimes update policies to lessen these burdens. Because of that, keep yourself and your organisation updated with these changes. Work with them as closely as possible.
Conclusion
Those are the four steps to optimise your drug development process, particularly during clinical trials or research. Of course, this list isn’t inclusive, and there are many ways to optimise your research and trials further. After all, each drug is unique, and each of them may require different techniques to help you make your medicine see the light of day in pharmacies and other medical institutions.
