
Drug Delivery
We can help you address the challenges in your drug delivery project and drive forward the development of next-generation devices and solutions for on-body and off-body treatments.

We develop next-generation drug delivery solutions for our clients.
Pharmaceutical companies face substantial challenges, from constraints in health spending to weakening drug pipelines. Yet opportunities exist for those bold enough to adapt, ranging from connected devices that drive adherence to generic devices at cost points previously thought impossible.
TTP is working with clients at all stages of the product development life cycle. From helping companies to explore and define new business opportunities, through to using a first principles approach to troubleshoot late stage problems in scale-up and commercialisation. But in all cases using highly skilled, multidisciplinary teams to develop market leading products and services routinely.
Why TTP
Large Volume Delivery
We specialise in the delivery of large-volume formulations and understand the constraints, and trade-offs, of large-volume, high-viscosity injectors and devices in order to rapidly bring solutions to market.
Connected Digital Health Ecosystem
We leverage our expertise in human factors, biomechanics, and engineering to deliver connected drug delivery injectors, inhalers, and other devices that can fit into large and complex digital health ecosystems and patient workflows.
Adherence Modelling for Sustainable Innovation
We understand the value of adherence models to drive sustainable innovation. At TTP, we use complex behavioural science to underpin our adherence model in order to create better interventions, design future disease management solutions, predictive models, and valuable decision-making tools.
TTP’s adherence modelling provides clients with holistic thinking and insight into their connected device developments for sustainable innovation.
Case studies
News & Insights
A model for predicting and improving medication adherence
Medication adherence is often studied after a drug or delivery device has been developed, but what if we were able to predict levels of adherence for a particular drug delivery device during development?
Developing digital health solutions with meaningful healthcare data
Developers of digital health technologies are racing to innovate and improve healthcare. But do they always know enough about the data their platform will be delivering to healthcare professionals to build a digital health solution that will be successful?
How branded healthcare devices can compete against generics
In a landscape of growing competition and new distribution channels, how can branded pharmaceutical devices compete against their generic counterparts? It turns out the answer is quite simple: by leveraging the one asset a generic product doesn’t have – brand.
Remote user testing for medical device development: advantages as well as challenges abound
Remote user testing allowed us to substantially accelerate the development of the CoVent™ ventilator. Dan Lock reviews the impact of social distancing on user research and finds that many of our necessary adaptations will continue to have value. Yet, each new study challenges us to come up with new approaches to inform medical device development.
R&D challenges for the success of microneedle systems
Microneedle systems pose multidisciplinary R&D challenges—some because of and some despite the much smaller size of the needles involved. But microneedle systems also offer exciting new prospects for drug delivery and multiplex biomarker detection. This information could be used to guide personalised treatment or enable value-based healthcare.
Ethical challenges in AI-driven diagnosis and healthcare
The use of artificial intelligence (AI) to aid medical diagnosis or rationalise healthcare raises similar ethical challenges as applications of AI in other industries, bias and discrimination among them. A prescription of selective forgetfulness for the AI may be a remedy, argue Roderick van den Bergh and Desmond Cheung.