11.5 Clinical trials

Clinical trials are crucial for evaluating new medical treatments. They progress through phases, from small safety studies to large efficacy trials, before a drug can be approved. Each phase builds on the previous, gathering more data on safety, dosing, and effectiveness.

Trials must be designed ethically and scientifically to protect participants and generate valid results. Key considerations include randomization, blinding, sample size, and appropriate controls. Regulatory oversight and statistical analysis ensure trials meet rigorous standards before new treatments reach patients.

Phases of clinical trials

Phase 0: Exploratory trials

Top images from around the web for Phase 0: Exploratory trials

• 

  Frontiers | Implementation of a Physiologically Based Pharmacokinetic Modeling Approach to Guide ... View original

  Is this image relevant?

• 

  Frontiers | Application of Pharmacokinetic-Pharmacodynamic Modeling in Drug Delivery ... View original

  Is this image relevant?

• 

  Frontiers | Implementation of a Physiologically Based Pharmacokinetic Modeling Approach to Guide ... View original

  Is this image relevant?

• 

  Frontiers | Application of Pharmacokinetic-Pharmacodynamic Modeling in Drug Delivery ... View original

  Is this image relevant?

1 of 2

Top images from around the web for Phase 0: Exploratory trials

• 

  Frontiers | Implementation of a Physiologically Based Pharmacokinetic Modeling Approach to Guide ... View original

  Is this image relevant?

• 

  Frontiers | Application of Pharmacokinetic-Pharmacodynamic Modeling in Drug Delivery ... View original

  Is this image relevant?

• 

  Frontiers | Implementation of a Physiologically Based Pharmacokinetic Modeling Approach to Guide ... View original

  Is this image relevant?

• 

  Frontiers | Application of Pharmacokinetic-Pharmacodynamic Modeling in Drug Delivery ... View original

  Is this image relevant?

1 of 2

• Conducted before traditional Phase 1 to assess pharmacokinetics and pharmacodynamics
• Involve a small number of participants (10-15) and use subtherapeutic doses
• Help determine if the drug behaves as expected in the human body (bioavailability, half-life)
• Provide early insight into the drug's mechanism of action and potential side effects
• Examples include microdosing studies with radiolabeled drugs and pharmacodynamic assays

Phase 1: Safety and dosage

• Primary goal is to assess safety and tolerability of the drug in humans
• Typically involve 20-100 healthy volunteers or patients with the target condition
• Determine the maximum tolerated dose and identify any dose-limiting toxicities
• Evaluate the drug's pharmacokinetics (absorption, distribution, metabolism, excretion)
• Establish a safe dose range for future trials and identify potential side effects to monitor

Phase 2: Efficacy and side effects

• Assess the drug's efficacy and further evaluate its safety in a larger patient population
• Typically involve 100-300 patients with the target condition and use randomized controlled designs
• Determine the optimal dose and dosing regimen for efficacy while minimizing side effects
• Identify the most relevant efficacy endpoints and measures for the target condition
• Examples include proof-of-concept studies, dose-ranging studies, and pilot studies

Phase 3: Efficacy vs standard treatment

• Confirm the drug's efficacy, safety, and overall benefit-risk profile in a large patient population
• Typically involve 300-3,000 patients and use randomized, double-blind, controlled designs
• Compare the drug's efficacy and safety to the current standard treatment or placebo
• Assess the drug's efficacy in different patient subgroups and identify any rare side effects
• Examples include pivotal trials for regulatory approval and comparative effectiveness studies

Phase 4: Post-marketing surveillance

• Conducted after the drug has been approved and marketed to monitor its long-term safety and efficacy
• Involve a large and diverse patient population in real-world settings (observational studies, registries)
• Identify any rare or long-term side effects not detected in earlier trials
• Evaluate the drug's effectiveness in different patient populations and treatment settings
• Examples include pharmacovigilance studies, comparative effectiveness research, and health outcomes studies

Design of clinical trials

Randomized controlled trials

• Gold standard design for assessing the efficacy and safety of interventions
• Participants are randomly assigned to receive the intervention or a control (placebo or standard treatment)
• Randomization minimizes bias and ensures that treatment groups are balanced for known and unknown factors
• Enables causal inference about the intervention's effects by controlling for confounding variables
• Examples include parallel group designs, crossover designs, and cluster randomized trials

Blinding in clinical trials

• Procedure in which one or more parties involved in the trial are unaware of the treatment assignment
• Single-blinding: participants are unaware of their treatment assignment (used when blinding investigators is not feasible)
• Double-blinding: both participants and investigators are unaware of the treatment assignment (gold standard)
• Triple-blinding: participants, investigators, and data analysts are unaware of the treatment assignment
• Blinding minimizes bias in the assessment of outcomes and ensures that expectations do not influence results

Placebo vs active control

• Placebo control: participants receive an inactive substance or sham procedure identical in appearance to the intervention
  • Used when no standard treatment exists or when withholding treatment is ethically acceptable
  • Enables assessment of the intervention's true effect by controlling for placebo effects and natural history
• Active control: participants receive a standard treatment or another active intervention
  • Used when a standard treatment exists and withholding it would be unethical
  • Enables assessment of the intervention's efficacy and safety relative to the current standard of care

Inclusion and exclusion criteria

• Predefined characteristics used to determine eligibility for participation in a trial
• Inclusion criteria: characteristics that participants must have to be eligible (age, diagnosis, disease severity)
• Exclusion criteria: characteristics that disqualify participants from eligibility (comorbidities, contraindications)
• Ensure that the trial population is representative of the target population and minimize confounding factors
• Balance the need for homogeneity (to detect treatment effects) and generalizability (to apply results to real-world patients)

Sample size determination

• Process of calculating the number of participants needed to detect a clinically meaningful treatment effect
• Based on the expected effect size, variability of the outcome measure, type I and II error rates, and power
• Larger sample sizes are needed to detect smaller treatment effects or to account for greater variability
• Insufficient sample sizes may lead to false negative results, while excessive sample sizes may be unethical and wasteful
• Examples of methods include power analysis, precision analysis, and adaptive designs

Ethical considerations

Informed consent process

• Procedure by which potential participants are fully informed about the trial and voluntarily agree to participate
• Involves providing information about the trial's purpose, procedures, risks, benefits, and alternatives
• Ensures that participants understand the information and have the capacity to make a voluntary decision
• Documented using a written informed consent form that is signed by the participant and the investigator
• Ongoing process that allows participants to ask questions and withdraw from the trial at any time

Protection of vulnerable populations

• Special considerations for individuals who may be more susceptible to coercion or exploitation (children, pregnant women, prisoners)
• Requires additional safeguards to ensure that participation is voluntary and that risks are minimized
• May involve obtaining assent from the participant in addition to consent from a legally authorized representative
• Requires justification for including vulnerable populations and a favorable risk-benefit ratio
• Examples include pediatric trials, trials in developing countries, and trials in emergency settings

Data safety and monitoring

• Process of ongoing review of trial data to ensure the safety of participants and the integrity of the data
• Involves regular review of adverse events, safety endpoints, and efficacy endpoints by an independent committee
• May involve predefined stopping rules for early termination of the trial if safety or efficacy concerns arise
• Ensures that participants are not exposed to unnecessary risks and that the trial is conducted according to the protocol
• Examples include data safety monitoring boards, clinical events committees, and futility analyses

Institutional review boards

• Independent committees that review and approve the ethical and scientific aspects of clinical trials
• Composed of scientific, medical, and lay members who are not involved in the trial
• Ensure that the trial is ethically justified, that risks are minimized and reasonable in relation to benefits
• Review the informed consent process and materials to ensure that they are complete and understandable
• Provide ongoing oversight of the trial and review any amendments or safety reports
• Examples include local IRBs, central IRBs, and ethics committees

Regulatory aspects

FDA oversight and guidance

• The FDA regulates clinical trials of drugs, biologics, and devices to ensure their safety and efficacy
• Provides guidance documents on the design, conduct, and reporting of clinical trials (ICH GCP, FDA GCP)
• Requires that trials be conducted under an investigational new drug (IND) application or investigational device exemption (IDE)
• Reviews trial protocols, informed consent forms, and safety reports to ensure compliance with regulations
• Conducts inspections of trial sites and sponsors to verify the integrity of the data and the protection of participants

Investigational new drug application

• Application submitted to the FDA to obtain permission to conduct clinical trials of a new drug or biologic
• Includes information on the drug's chemistry, manufacturing, and controls, as well as preclinical and clinical data
• Requires a detailed protocol describing the trial's objectives, design, endpoints, and statistical analysis plan
• Must be approved by the FDA before the trial can begin enrolling participants
• Amendments must be submitted for any changes to the protocol or safety information

New drug application process

• Application submitted to the FDA to obtain approval to market a new drug or biologic
• Includes comprehensive data from all phases of clinical trials demonstrating the drug's safety and efficacy
• Requires detailed information on the drug's manufacturing, labeling, and postmarketing surveillance plans
• Reviewed by a team of FDA scientists and medical experts to determine if the benefits outweigh the risks
• May require additional trials or postmarketing studies to address any outstanding questions or concerns
• Examples include priority review for drugs that address unmet medical needs and accelerated approval for drugs that treat serious conditions

Nanomedicine in clinical trials

Nanoformulations of existing drugs

• Nanotechnology can be used to improve the delivery and efficacy of existing drugs
• Nanoformulations can increase the drug's solubility, stability, and bioavailability, allowing for lower doses and reduced side effects
• Examples include liposomal doxorubicin (Doxil) for ovarian cancer and albumin-bound paclitaxel (Abraxane) for breast cancer
• Clinical trials are needed to demonstrate the safety and efficacy of nanoformulations compared to the original drug
• Challenges include optimizing the nanoformulation's properties and scaling up manufacturing for clinical use

Novel nanotherapeutics and diagnostics

• Nanotechnology enables the development of novel therapeutic and diagnostic agents with unique properties
• Examples include targeted nanoparticles that deliver drugs specifically to cancer cells and magnetic nanoparticles for enhanced MRI contrast
• Clinical trials are needed to demonstrate the safety and efficacy of these novel agents in humans
• Challenges include optimizing the nanoparticle's design and function, assessing their biodistribution and clearance, and evaluating any long-term toxicities
• Examples include BIND-014, a targeted docetaxel nanoparticle for solid tumors, and Cornell dots, a silica nanoparticle for cancer imaging

Challenges of nanomedicine development

• Nanomedicines face unique challenges in their development and translation to clinical use
• Nanoparticles' small size and high surface area can lead to unexpected biological interactions and toxicities
• The lack of standardized characterization methods and regulatory guidelines can hinder the development and approval of nanomedicines
• The complex manufacturing and scale-up processes can increase costs and limit the availability of nanomedicines
• The need for interdisciplinary collaboration among scientists, engineers, and clinicians can slow down the development process

Successful nanomedicine case studies

• Despite the challenges, several nanomedicines have successfully completed clinical trials and received regulatory approval
• Doxil, the first FDA-approved nanodrug, has been used to treat ovarian cancer and Kaposi's sarcoma since 1995
• Abraxane, an albumin-bound paclitaxel nanoparticle, was approved for breast cancer in 2005 and has since been approved for other cancers
• Onivyde, a liposomal irinotecan formulation, was approved for pancreatic cancer in 2015 and has shown improved survival compared to standard therapy
• These success stories demonstrate the potential of nanomedicine to improve patient outcomes and inspire further research and development in the field

Statistical analysis

Hypothesis testing and p-values

• Statistical hypothesis testing is used to determine if the observed treatment effect is likely due to chance or a true difference
• The null hypothesis (H0) states that there is no difference between the treatment groups, while the alternative hypothesis (H1) states that there is a difference
• The p-value represents the probability of observing the treatment effect or a more extreme one if the null hypothesis is true
• A small p-value (typically < 0.05) suggests that the observed effect is unlikely due to chance and supports rejecting the null hypothesis
• Examples of hypothesis tests include t-tests for continuous outcomes, chi-square tests for categorical outcomes, and log-rank tests for time-to-event outcomes

Efficacy endpoints and measures

• Efficacy endpoints are the outcomes used to assess the treatment's effect on the target condition
• Primary endpoints are the main outcomes used to evaluate the trial's objectives and determine the sample size
• Secondary endpoints are additional outcomes that provide supportive evidence or explore other aspects of the treatment's efficacy
• Efficacy measures can be clinical (survival, symptoms), biological (biomarkers, imaging), or patient-reported (quality of life, functioning)
• The choice of endpoints and measures depends on the target condition, the treatment's mechanism of action, and the trial's objectives
• Examples include overall survival for cancer trials, hemoglobin A1c for diabetes trials, and the 6-minute walk test for heart failure trials

Safety data and adverse events

• Safety data include any untoward medical occurrences that occur during the trial, regardless of their relationship to the treatment
• Adverse events are classified by their severity (mild, moderate, severe), seriousness (life-threatening, disabling, requiring hospitalization), and relatedness to the treatment (definitely, probably, possibly, unlikely, unrelated)
• The incidence, severity, and relatedness of adverse events are compared between the treatment groups to assess the treatment's safety profile
• Serious adverse events and suspected unexpected serious adverse reactions (SUSARs) must be reported to the sponsor, IRB, and regulatory authorities within specified timeframes
• Examples of common adverse events include headache, nausea, and injection site reactions, while examples of serious adverse events include anaphylaxis, myocardial infarction, and cancer

Subgroup analysis and stratification

• Subgroup analysis involves evaluating the treatment effect in specific subsets of the trial population defined by baseline characteristics (age, sex, disease severity)
• Stratification involves balancing the treatment groups for important baseline characteristics to ensure that they are evenly distributed
• Subgroup analysis can identify populations that may benefit more or less from the treatment, or that may be at higher risk for adverse events
• Stratification can improve the trial's power to detect treatment effects and reduce confounding by important prognostic factors
• However, subgroup analyses are often exploratory and may be underpowered, leading to false positive or false negative results
• Examples of common subgroups include age (pediatric, adult, geriatric), sex (male, female), and disease stage (early, advanced)

Clinical trial management

Protocol development and amendments

• The clinical trial protocol is the document that describes the trial's objectives, design, procedures, and statistical analysis plan
• Protocol development involves collaboration among the sponsor, investigators, and other stakeholders to ensure that the trial is scientifically valid, ethically justified, and feasible
• The protocol must be approved by the IRB and regulatory authorities before the trial can begin enrolling participants
• Protocol amendments may be necessary during the trial to address any changes in the trial's design, procedures, or safety information
• Amendments must be reviewed and approved by the IRB and regulatory authorities before they can be implemented
• Examples of common protocol amendments include changes in eligibility criteria, dosing regimens, and safety monitoring plans

Site selection and monitoring

• Site selection involves identifying and recruiting clinical sites that have the necessary expertise, resources, and patient population to conduct the trial
• Sites are evaluated based on their experience, performance, and compliance with regulations and good clinical practices
• Site initiation visits are conducted to train the site staff on the protocol, procedures, and data collection methods
• Site monitoring involves ongoing oversight of the site's performance and compliance throughout the trial
• Monitors review the site's study records, observe study procedures, and verify the accuracy and completeness of the data
• Examples of common monitoring activities include source data verification, drug accountability, and adverse event reporting

Patient recruitment and retention

• Patient recruitment involves identifying and enrolling eligible participants who meet the trial's inclusion and exclusion criteria
• Recruitment strategies can include advertising, referrals from healthcare providers, and community outreach
• Retention involves keeping participants engaged and motivated to complete the trial's procedures and follow-up visits
• Retention strategies can include providing incentives, minimizing participant burden, and maintaining regular communication
• Recruitment and retention can be challenging, especially for trials of rare diseases or underserved populations
• Examples of common recruitment and retention challenges include lack of awareness, mistrust of research, and competing priorities

Data collection and validation

• Data collection involves capturing the trial's endpoints and other relevant information from participants, healthcare providers, and other sources
• Data can be collected using paper or electronic case report forms, patient diaries, and other tools
• Data validation involves checking the data for accuracy, completeness, and consistency
• Validation can be done using manual or automated methods, such as range checks, logic checks, and source data verification
• Data queries are generated for any discrepancies or missing information and must be resolved by the site staff
• Examples of common data collection and validation challenges include missing data, data entry errors, and protocol deviations

Reporting and publication

Clinical study reports

• Clinical study reports are comprehensive documents that describe the trial's methods, results, and conclusions
• Reports are prepared by the sponsor and submitted to regulatory authorities as part of the marketing application
• Reports include detailed information on the trial's design, conduct, and analysis, as well as any protocol deviations or safety issues
• Reports are reviewed by regulatory authorities to determine if the trial's results support the drug's safety and efficacy
• Examples of common sections in a clinical study report include the synopsis, introduction, trial objectives, trial design, trial results, and conclusion

Peer-reviewed journal articles

• Peer-reviewed journal articles are the primary means of disseminating the trial's results to the scientific community
• Articles are written by the trial's investigators and submitted to relevant scientific journals for publication
• Articles undergo peer review by independent experts in the field to ensure their scientific validity and importance
• Articles include a structured abstract, introduction, methods, results, and discussion sections
• Examples of common journals for publishing clinical trial results include the New England Journal of Medicine, Lancet, and JAMA

Public registration of trials

• Public registration of clinical trials is required by law and ethical guidelines to promote transparency and accountability
• Trials must be registered on publicly accessible databases such as ClinicalTrials.gov before enrolling the first participant
• Registration includes information on the trial's objectives, design, elig