SmartDose: Medication management service based on additive manufacturing
Age UK estimates that almost two million people over 65 are likely to be taking at least seven prescribed medicines. This number doubles to approaching four million for those taking at least five medicines. In England overall, more than one in ten people aged over 65 takes at least eight different prescribed medications weekly, and this increases to one in four among people who are aged over 85.
A smart medication management solution for the elderly or their carers, who must take/administer regular medication during the day but have trouble in remembering what to take and when to take it is needed. The current additive drug delivery systems have technical limitations;
- High temperature processing degrades drugs and hot melt extrusion is done on readily available filaments instead of raw ingredients.
- No inline quality measurement systems (physical/chemical/mechanical properties of tablets)
- No post print curing or drying, very important to avoid sticking and picking defect and to obtain consistent dose
- No inline surface characterisation:
Smartdose proposes an integrated system capable of coating, drying, and measuring the characteristics of the tablets manufactured using 3D printing. System for in-situ assessment of physical-mechanical properties of the tablet can be of high demand. For example, key challenges related to metrological aspects of these drug delivery systems are not up to the mark:
- In-situ metrological quality assurance, monitoring and control towards optimizations,
- Real time post finishing, coating, and post drying capabilities
- In-situ chemical and mechanical characterization of the medicine for optimal dosage
SmartDose will focus on developing a technique that combines power ultrasonic excitation with 3D printing of drugs to eliminate the defects. The drugs using this process will also be customised for every user depending on the age and GP's recommendation. A reverse optimisation model running alongside these techniques will enable printing of the drugs at local pharmacies. This technology combined with a smart pill dispenser will be able to ensure that the elderly won't miss a dose or take an incorrect dose. The objectives of this research can be summarised as follows:
- Develop a new additive manufacturing system capable of delivering personalised medicine and perform medication management.
- Develop a 3D printing technology capable processing raw material instead of filaments at reduced temperatures
- Perform in-situ quality control of the manufactured drugs
- Improve the efficiency of the printing process using power ultrasound.
A smart pill dispenser will be developed that will be capable of holding two weeks’ worth of personalised prescribed medication and dispenses the right pill at the right time. The dispenser will notify the user at the right time through an alarm in the box as well as a notification on a smartphone. Through a smartphone companion app, the dispenser will detect if the user has not used a drug at the appropriate time because they missed the alarm. The data about consistent usage of drugs is transferred to next-of-kin or a doctor to allow monitoring the consistent usage of medicine.
The SmartDose project is a breakthrough development. SmartDose will have a big impact on how doctors can treat their aging patients. Being able to specify the dosage that a patient will take at a time of day, as well as the shapes, colours, and sizes, based on an individual patient’s needs. This will remove the limit of adhering to the dosage set by pharmaceutical companies, it will also stop patients breaking pills in half to reduce the dosage.
SmartDose will also dramatically change the service that pharmacies can provide to their customers, while also changing the supply chain for pharmaceutical material providers, pharmaceutical companies, drug manufacturers, distributors, repackaging companies, etc.
Brunel Innovation Centre's Role
Brunel Innovation Centre (BIC) will contribute the ultrasonic extrusion system they developed for 3D Printing for improving material distribution and flow in additive manufacturing processes. BIC will also work on improving in-situ analysis algorithms and image processing to ensure the quality of the medicines delivered.
The NIR (Near Infrared) system will generate data that will be analysed by BUL intelligent algorithms to characterise the printed medication and ensure the quality of the tablet. The ultrasonic excitation will also affect how the medication is printer and how the material sets. Machine Learning will be used to optimise the process to ensure a continuous high-quality output.
FABRX LIMITED (Lead) https://www.fabrx.co.uk/
BRUNEL UNIVERSITY LONDON
Meet the Principal Investigator(s) for the project
Professor Tat-Hean Gan - Professional Qualifications CEng. IntPE (UK), Eur Ing BEng (Hons) Electrical and Electronics Engg (Uni of Nottingham) MSc in Advanced Mechanical Engineering (University of Warwick) MBA in International Business (University of Birmingham) PhD in Engineering (University of Warwick) Languages English, Malaysian, Mandarin, Cantonese Professional Bodies Fellow of the British Institute of NDT Fellow of the Institute of Engineering and Technology Tat-Hean Gan has 10 years of experience in Non-Destructive Testing (NDT), Structural Health Monitoring (SHM) and Condition Monitoring of rotating machineries in various industries namely nuclear, renewable energy (eg Wind, Wave ad Tidal), Oil and Gas, Petrochemical, Construction and Infrastructure, Aerospace and Automotive. He is the Director of BIC, leading activities varying from Research and development to commercialisation in the areas of novel technique development, sensor applications, signal and image processing, numerical modelling and electronics hardware. His experience is also in Collaborative funding (EC FP7 and UK TSB), project management and technology commercialisation.
Related Research Group(s)
Brunel Innovation Centre - A world-class research and technology centre that sits between the knowledge base and industry.
Project last modified 07/06/2021