Lecture 11: Biomarkers

Block 4

What is a Biomarker

• A characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention

  • definition created by a working group in the early 200s

• Want to be objective and measurable

• Introduced in early-mid 2000s and present early on in drug development process and lead optimisation stages

Uses of Biomarkers

• Dependent on the project and stage of drug development

• Aim for translational biomarkers that can be applied in the clinic.

• Different naming conventions depending on function

Diagnostic Biomarker

• Indicates presence of disease

  • E.g. missing in psychiatry – relies on symptoms reported by patients

Susceptibility or Risk Biomarker

• Indicates potential for developing disease

Predictive Biomarker

• Predicts who will respond well or poorly to treatment

Prognostic Biomarker

• Predicts and monitors disease recurrence or progression

  • Looks at the journey of a disease

• e.g. predicts cancer recurrence or life expectancy

Pharmacodynamic (Response) Biomarker

• Confirms a biological response to the drug

• Ensure that the drugs targets the correct mechanisms to produce a given therapeutic response

Monitoring Biomarker

• Assess the effect of a drug on disease/ condition → monitors a disease and treatment responses overtime

Saftey Biomarker

• Predicts toxicity or side effects of a drug

  • Ubrella term - many different markers can be assesseed

Early History of Biomarkers and Initial Clinical Use

• Ancient Chinese, Greek, Egyptian, and Indian medicine first noted biomarkers.

• Used to measure heart rate and blood pressure – physiological indicators of cardiovascular function.

• These evolved into modern clinical tests, like cholesterol level monitoring.

• Enabled basic tracking of physiological health long before molecular markers were discovered.

The Omics Revolution

• Occured in the early 2000s and allowed for the

  • Identification of novel targets

  • Better understanding of disease processes

  • Genomics, proteomics, metabolomics

  • “Molecular medicine” evolves

    • This underpins the idea of biomarkers

Biomarker Revolution (2000’s)

• Driven by personalised and precision medicine, rooted in the omics revolution (DNA, genes, proteins).

• Advancing technologies allowed for faster and more accurate visualisation of biological targets.

• Enabled quantification of effects on those targets.

• Biomarkers now offer reliable measurement and quantification of biological responses.

• Can be done rapidly, cheaply, and at scale due to tech advancements.

Need for Biomarkers

• Faster and more accurate diagnoses, including in mental health.

  • Greater range of diagnostic tools

  • In cancer, it helps identify the specific gene driving the disease, enabling targeted and focused drug design.

• Improves clinical management by identifying which patient groups will benefit most—more personalised and effective treatments.

  • better clinical practice - good patient-physician outcome, as more likely to treat the disease

• Expedites the discovery of new treatments by guiding quicker, evidence-based decisions—focuses on drugs likely to succeed.

• Aids in evaluating new treatments, improving outcomes for both physicians and patients.

How do biomarkers impact the probability of successful drug development?

• Biomarkers increase the chance of progression through drug development stages.

• Without biomarkers: up to 90% attrition rate — only 1 in 10 drugs succeed in clinical trials.

• With biomarkers: success rate increases to nearly 25%.

• "Attrition" = failure to progress through development stages.

Translational Biomarkers

• Biomarkers used from basic research through to clinical application.

• They help assess how effective a drug is.

• If a drug isn’t promising, they allow early termination of development (cost-effective).

• It can provide information and generate feedback about the drug in clinical trials and when on the market, allowing for improvements and better therapies

Biomarker Discovery and Developemnt

• Biomarkers must go through discovery, validation, and qualification phases to be accepted by regulatory authorities

• Validation requires strong evidence that the marker is real, reproducible, and repeatable.

• Regulatory authorities (e.g., FDA) have a list of accepted biomarkers.

• Validation is challenging

  • Many altered genes may be identified in a disease, but proving consistent, population-wide effects is difficult.

  • Especially in psychiatric disorders, genetic changes can vary even among patients with the same symptoms, making a single, consistent biomarker hard to define.

FDA's Critical Path Opportunities List

• Created in 2004 in response to high attrition rates in drug development.

• Designed to speed up the development and approval of new drugs.

• Encourages the development of biomarker strategies alongside drug development to improve predictions of drug efficacy.

• Goal: Move beyond relying on conventional clinical endpoints (e.g., waiting until death) to more accurate, earlier measures.

How Do Biomarkesr Help Drug Development

• Biomarkers allow for the pre-clinical identification of whether a drug will work and whether this translates over into clinical development and mass market, potentially improving the success of drug development.

• They help identify candidate drugs that are likely to fail earlier in the process, reducing costs and increasing efficiency.

• They also help predict drug efficacy before reaching clinical endpoints, allowing for more accurate development timelines.

Objectives and Issues in Drug Development

• Objective measurements - need to make reliable measurements and move confidently from one development stage to the next.

• However to determine clinical utility, drugs often need to be tested for an extended period, which is not possible in clinical trials due to time constraints.

  • Clinical endpoints (e.g., effectiveness, safety) often take too long to observe.

• Solution: The use of biomarkers can provide quicker assessments, enabling earlier translation of findings and speeding up the drug approval process; hence translation is important

Importance of Translational Biomarkers

• Biomarkers that can be observed across different stages (in vitro, in vivo, animals, and humans) to determine if the drug will be effective in humans.

  • Importance: If results differ between stages, the drug is unlikely to be effective in humans, helping narrow down viable drug options in LO.

Types of Translational Biomarkers in Drug Development:

• Toxicity Biomarkers: Used towards the end of drug development to assess potential harmful effects.

• Target Engagement Biomarkers: Evaluated early in drug discovery to assess if the drug engages the target.

• Mechanism Biomarkers: Monitored throughout different pre-clinical stages to assess how the drug works.

Toxicity Biomarker

• A negative biomarker that if achieved, stops drug development

  • Has negative rather than positive implications if achieved

• Used for “STOP” decision for a candidate compound

Examples of Toxicity Biomarkers

• QT prolongations and hERG channel blockade

  • Cases of fatal arrhythmia (TdP) and sudden cardiac arrest

  • Binding to hERG channel is assessed pre-clinically; if a drug binds at certain concentrations, development is halted → channel binding is a critical "go/no-go" decision in drug development.

  • Ion channel activity and electrophysiology tests can be used

• Liver Toxicity: Look at liver function tests and enzyme ratios to assess liver health

  • If liver enzymes are high, it can indicate damage and toxicity

• Kidney Toxicity: enzyme levels and glomerular filtration rate are monitored

  • Deviation from a given threshold can indicate damage

• Liver and kidney toxicity testing can be performed in vitro or using animal models, with biomarkers in the blood being analysed.

Target Engagement Biomarker

• Assesses whether a candidate compound interacts with a macromolecular target (e.g., receptor or enzyme).

• Confirms the drug's interaction with the target and determines if it is likely to have a therapeutic effect.

  • Can reveal whether a certain level of the drug is required to have an effect, if this doesn’t occur in humans the drug wont progress

• Helps validate the drug’s mechanism of action and ensures the drug can be progressed through clinical stages.

• Validates this interaction between different models of testing

Assesments of Target Engagement in CNS Drug Development

• Imaging Techniques Used:

  • PET (Positron Emission Tomography)

  • SPECT (Single-Photon Emission Computed Tomography)

• These imaging methods provide insight into how a drug interacts with specific receptors or enzymes in both animal models and humans.

• In CNS drug development, imaging reveals how a drug binds to D2 receptors, crucial for evaluating antipsychotic effect

What does binding occupancy reveal in the context of target engagement, and what is its significance

• Binding Occupancy refers to the proportion of receptors occupied by the drug.

• For antipsychotic drugs, 65-80% occupancy of D2 receptors is needed to achieve a therapeutic effect without causing side effects like extrapyramidal symptoms.

• Helps determine whether a drug will work in humans based on binding activity observed in animal models.

  • if not, the drug won’t be progressed

How does target engagement validate or invalidate drug-biomolecule relationships in drug development?

• Validation: Confirms that a drug interacts with the intended biomolecule (receptor or enzyme) and elicits the desired response that can be related to disease states in in vivo responses

• Invalidation: If the drug does not bind adequately or has a poor effect in humans, it may be discarded from development.

• Target engagement can either strengthen the development of a drug or indicate its failure to progress.

Mechanism Biomarker

• Looks at something downstream of the target

• Physiological impact of the candidate compound

• Measures changes in specific events downstream of target engagement – assess if the drug has a functional effect:

  • Enzyme activity

  • Gene, protein expression

  • Behavioural changes

  • Blood concentration of specific chemicals e.g. cholesterol

• Requires something that can be measured e.g. from the blood urine and saliva etc from a patient to assess whether the mechanism of the drug is functionally efficacious

Outcome Biomarker

• Tells us whether a drug is efficacious and produces the desired response

  • a physiological measure of the response needed to treat a given disease

  • May look at outcomes within the disease or another form of efficacy related to the disease

• Also known as:

  • Disease-related biomarkers

  • Efficacy biomarker

• Defined link with the disease that predicts candidate compound efficacy

  • Can be biochemical

  • Can be physiological

    • BP changes

    • Sleep induction

How did the HIV/AIDS epidemic influence drug development, and what role did biomarkers play?

• In the 80s and 90s, the HIV/AIDS epidemic created a need for rapid drug development due to high mortality, particularly from Kaposi sarcoma.

• HIV was isolated and identified in 1982, linked to a decrease in CD4 T-helper cells, which was used as a biomarker in assays

  • Found that HIV progressed to AIDs, which caused those deaths

• The decrease in CD4 T-helper cells led to the development of the first drug, AZT, which aimed to increase these CD4+ T-cells.

• Later, measuring HIV RNA levels became a better indicator of viral load and disease progression.

• Biomarkers like CD4 counts and RNA levels accelerated the development of over 30 HIV drugs.

Surrogate End Point

• Used to replace true clinical endpoints, allowing earlier decision-making in drug development.

• Example: CD4 T-helper cell count was initially used as a surrogate endpoint in HIV treatment.

• As HIV progressed to AIDS, the viral RNA load became a better indicator of whether this occurred, providing better insight into drug effectiveness, prognosis and disease progression.

How could biomarkers have helped prevent issues in drug safety and clinical trials?

• Biomarkers could have helped prevent the withdrawal of drugs and serious adverse effects in clinical trials.

• 34 drugs were withdrawn from the market between 1995-2005, e.g., Rofecoxib COX-2 inhibitor for pain (Vioxx®), was withdrawn due to fatal side effects.

• In the case of TGN1412 monoclonal antibody (2006), biomarkers could have identified risks before severe adverse effects occurred.

  • Monkeys used in toxicity testing showed no adverse effects, but humans suffered major cytokine storms due to differences in CD28 immune cell expression, which led to serious health issues.

Weakness of Biomarker Use in Drug Development

• Difficult to measure

• Expensive to implement

• Require long experiments

• Difficult to reproduce

Strength of Biomarker Use in Drug Development

• Easily measured

• Time-efficient – used in real-time to help make decisions

• Quantitative

• Objective

  • Want to remove subjective impression

• Highly reproducible

• Clinical relevance and reliability across heterogeneous/diverse patient populations

  • If it reveals that the drug is more advantageous in a particular demographic, targeting it to the right people in clinical trials

Pharmacogenomics BIomarkers

• Informative in a clinical setting, revealing from a person’s genomic makeup whether a drug will be effective.

• Help identify if a particular gene drives a disorder or is responsible for drug metabolism.

• Guide drug suitability and dosage adjustments based on individual genetic profiles.

• In clinical trials, it can help to identify patient cohorts with similar or differing responses to a drug and whether they possess or lack the drug target

• It can assess metabolism (e.g., whether a patient is a poor or ultra-rapid metaboliser) to avoid toxicity and ensure proper dosing.

Diagnostic Biomarkers

• Primarily used in a clinical setting to help diagnose a particular disorder

• Often overlaps with pharmacogenomic biomarkers, as the presence of a given gene can reveal a diagnosis for a particular disease, and can help to identify a disease much earlier and quickly

• Poor diagnostic markers for psychiatric and CNS disorders – diagnosis dependent on signs and symptoms – hard to physically measure something

• Can also be used in a preclinical in vivo setting

• Identify whether the disease is present or not

• Identify the risk of disease

• Identify progression/regression of the disease

• Identify the disease before the manifestation of symptoms

Companion Diagnostics

• Helps diagnose patients that the drug will be successful and effective in

• Test used to detect the drives or diagnosis of a disease – to allow for the right prescription

Complimentary Diagnostics

• Won’t give an ultimate diagnosis, but can give an indication as to whether a drug is likely to be effective and how effective it will be in an individual

  • Effective method employed when identifying genes that drive a particular cancer

  • For psychiatric disorders, there often isn’t a single gene driving the disorder – poor drug treatments and diagnostic/ companion diagnostic tests used for these types of disorders.

Personalised/ Precision Medicine

• Use of an individual’s unique molecular and genetic characteristics to allow

  • improved diagnosis

  • predict susceptibility to disease or treatment

  • refine doses to maximise successful outcome

  • minimise adverse reactions

Benefits of Biomarkers

• Biomarkers support the selection of drug candidates

• Biomarkers facilitate regulatory and development decisions.

• Precise patient stratification (trials and treatments)

• Biomarkers may be used as surrogate endpoints

• Biomarkers are helpful to determine the benefit-risk profile for a drug under development, thus allowing a more straightforward decision-making by regulatory agencies.