Why is patient safety compromised in the development of new medicines?

By Dr Jan Turner

Today is the inaugural #WorldPatientSafetyDay, the objective of which is to raise global awareness about patient safety and encourage global solidarity and action. So, from my perspective as Director of the Safer Medicines Trust, I would like to raise the subject of the safety of patients taking medicines. Yes, you heard me right. Keeping patients safe from the medicines they take, the same incredible medicines taken to treat, improve and cure disease and injury. The same pain killers taken for that headache, the antihistamines taken to rid us of the dreaded summer hay fever symptoms, or the life-saving medicines developed to treat cancer and heart disease. The same medicines that many believe to be thoroughly tested before they even get near a human. The same medicines that may sadly kill up to 10,000 people in the UK (1) or 100,000 in the US (2) annually from adverse drug reactions (ADRs) (a).

An inconvenient truth

The disturbing truth about medicines that many people are unaware of is that they all have the potential to harm and the way in which we test to see how extensive that harm may be has changed very little in the last 40 or so years.  Water has the potential to harm – in sufficient dose – as do household products, chemicals in the environment, ingredients in food and cosmetics. All medicines (and all other chemicals) are tested for toxicity (or safety) before they enter the market but within drug discovery, these tests have not sufficiently advanced over the years, despite incredibly innovative and representative models being developed.

In many cases, the medicines we take for granted will work as intended, without any harm being done. We may all, to some extent, suffer mild side effects (headaches, nausea, tiredness, etc) with medication. However, in a significant number of cases adverse drug reactions may occur causing significant individual suffering and, in some cases, severe life-threatening consequences. So how and why do these medicines get through the multi-billion-dollar pharmaceutical (pharma) drug discovery process and into the human population if they can cause such suffering? Well, current safety testing relies heavily on outdated models of disease and toxicity and invariably, these are not relevant to the human condition being investigated. Yet we continue to use data and information from those models to determine if a drug will work as intended (efficacy (b)) and be safe to use (non-toxic) in humans. Regulatory agencies, such as the FDA (Food and Drug Administration) in the US, the EMA (European Medicines Agency) in Europe and the MHRA (Medicines and Healthcare products Regulatory Agency) in the UK, are responsible for ensuring patient safety of any medical device or agent to be marketed in the world and they will examine the evidence from the pharma company’s pre-clinical and clinical trials before progressing a candidate drug through to market. That process however, is clearly broken, as the number of ADRs and the proportion of drugs being so-called “black-boxed (c)” or withdrawn post-launch, continues to increase (3).

Some of this failure can be attributed to differences in the genetic make-up of individuals leading to unpredictable ADRs.  Much can also be attributed to the outdated, non-human relevant models being used as proxies for a disease state, where differences in how a drug behaves in one animal species, for example, do not translate to how the drug behaves in a human (4). Even our closest relatives, the non-human primates, may metabolise or react to a drug in a completely different way from humans, with potentially disastrous consequences in terms of patient safety (5). Unfortunately, safety tests using a range of species including rats, mice, rabbits, dogs and non-human primates, have failed to prevent exposure of humans to unsafe medicines, which have subsequently harmed patients (6). In addition, the use of animals to create “models” of diseases such as stroke, cancer and Alzheimer’s, which in some cases only manifest in man, has left us with several thousand diseases affecting humans for which only ~500 are estimated to have any approved treatments (7).

Changing the paradigm

After 25 years of supporting drug discovery groups in pharma, developing platforms to speed the drug discovery process, tests to measure toxic endpoints and stem cell derived cells to improve the predictivity of potentially toxic drugs, I found myself wondering if anything has really changed in the testing of medicines to improve their efficacy and safety for humans? Pharma can now do things faster, they can test more compounds against a therapeutic target, and they know more about the biology behind therapeutic targets but disturbingly, there appears to be no increase in the productivity of drug discovery as a whole. Indeed, productivity is decreasing and is now at its lowest level in 9 years (8), with the cost of developing a new drug skyrocketing to over $2B (8). In addition, the number of new drugs being approved for market per $ spend continues to decrease (9).

Besides increasing costs and decreasing productivity, are pharma and the regulators doing everything possible to protect patient safety by continuing with the current paradigm for drug development? It is clear from numerous scientific papers, clinical studies, ADR reporting data and retrospective comparison studies that human relevant new approach methodologies (NAMs) (d) can help us to better understand human disease and better predict drug toxicity and some examples of the successful implementation of these methods in academic and non-regulatory settings are well established. Indeed in silico (e) computational methods, similar in principle to those used in facial recognition systems worldwide, already appear to offer a way to mimic human clinical trials for drugs that are potentially cardiotoxic by capturing numerous ECG traces and training algorithms to detect cardiotoxic markers within subsequent patient traces (10). And so called “organ on a chip” (OOC) technologies, where cells from specific tissues can interact with each other to represent miniature human organs in vitro (f) have also advanced in the last ten years to offer a way to mimic a whole organism’s response to a drug treatment, when combined with quantitative computational methods (11) . If in vitro and in silico human relevant approaches together offer a way to improve the prediction of a medicine’s potential harm, why are we still seeing unexpected toxicities when new drugs reach humans?

Insanity prevails?

As Einstein is often quoted as saying: “insanity is doing the same thing over and over again and expecting different results”. It seems to be a clear case of insanity, as defined by this quote, if the same legacy methods, which we know from real world clinical situations to be dangerously flawed, continue to be used to test the safety of human medicines. There are innovative technologies available to reduce the use of, or indeed replace, current methods but for them to be implemented and the safety of patients improved, we need regulators, pharma, patients, payers, and practitioners to adopt and champion these new methods until they are mandated for all new medicines. We all owe it to ourselves to be wiser about the ways in which drugs are tested and approved. After all, why on earth should we put our safety at risk when taking a medicine that we expect to help us, not harm us?

(a) Adverse drug reaction (ADR): An unexpected reaction caused by administration of a pharmaceutical drug

(b) Efficacy: the ability of a drug or treatment to produce the intended result

(c) Black-boxed: A black box warning or boxed warning is the U.S. Food and Drug Administration’s most serious warning for drugs and medical devices. A drug or device with a black box warning has side effects that may cause serious injury or death.

(d) New approach methodologies (NAMs): new scientific approaches that focus on human biological processes to investigate disease and potential treatments, using human cells, tissues, organs and existing data

(e) In silico: biological studies that are performed on a computer or using computer simulation or modelling

(f) In vitro: studies of biological properties that are conducted outside of a living organism, e.g. in a cell culture


  1. Pirmohamed M, James S, Meakin S, et al. Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients. BMJ. 2004;329(7456):15-9.
  2. Food and Drug Administration (FDA). Preventable Adverse Drug Reactions: A Focus on Drug Interactions. ADRs: Prevalence and incidence. 2019. [Accessed January 24 2019]
  3. Downing N S, et al. Postmarket Safety Events Among Novel Therapeutics Approved by the US Food and Drug Administration Between 2001 and 2010. JAMA. 2017;317(18):1854-1863. doi:10.1001/jama.2017.5150
  4. Pound P, Ritskes-Hoitinga M. Is it possible to overcome issues of external validity in preclinical animal research? Why most animal models are bound to fail. Journal of translational medicine. 2018;16(1):304.
  5. Attarwala H. TGN1412: From Discovery to Disaster. J Young Pharm. 2010 Jul-Sep; 2(3): 332–336. doi: 10.4103/0975-1483.66810
  6. Bailey J, Thew M and Balls M. Predicting Human Drug Toxicity and Safety via Animal Tests: Can Any One Species Predict Drug Toxicity in Any Other, and Do Monkeys Help? ATLA 43, 393–403, 2015.
  7. NCATS (National Center for Advancing Translational Science) Transforming Translational Science. Fall 2017. (accessed 17/5/2019)
  8. Deloitte. A new future for R&D? Measuring the return from pharmaceutical innovation 2017. 2017. Available from: (Accessed 17/5/19)
  9. BioIndustry Association and the Medicines Discovery Catapult. State of the discovery nation 2018 and the role of the Medicines Discovery Catapult. 2018. (Accessed 17/5/19)
  10. Passini E, Britton OJ, Lu HR, et al. Human in silico drug trials demonstrate higher accuracy than animal models in predicting clinical pro-arrhythmic cardiotoxicity. Frontiers in physiology. 2017; 8:
  11. Cirit M and Stokes C L. Maximizing the impact of microphysiological systems with in vitro–in vivo translation. Lab Chip, 2018, 18, 1831.

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