Development Of Medicine Flashcards

Question

Explain longitude or studies with mention to cohort study

Answer 1

Longitude or studies can be perspective or retrospective and show how a disease or treatment progresses over a period of time Cohort studies are when a group of people who are initially disease-free are followed over a study period of time this can be months days or years Framingham study of 5000 inhabitants of Massachusetts over a number of decades including their children and children spouses is a good example in the study of the risk factors for cardiovascular disease diseases

Answer 2

These are studies which draw conclusions on the cost effectiveness of different treatments which provide evidence to the UK health and technology assessment buddies and the institute for health and care excellence (NICE)

Answer 3

Results and criteria can greatly differ depending on the cohort of participants used as drugs react differently in young old etc due to this we have to think about participants deeply and consider the following. It is important to include many different backgrounds so the results mirror the people who are going to use Disease severity Disease duration Patient’s age Patient body mass Existing medicines, pregnancy risk factors for harmful reaction Number of disease episodes per year if recurrent

Answer 4

In a placebo trial a placebo and non-effective substance is given to patients and this is used as the baseline however ethically it’s deemed that people need to be treated regardless so instead Group a is the IMP and group B is a comparative drug already in the market and all group a has to do is prove non-inferiority or superiority

Answer 5

When neither the patient or doctor know which treatment the patient is the new medicine until the trial is finished To avoid bias in the person sorting the groups it is randomly assigned

Answer 6

Trial design must be shown Selection of subjects Treatment to be administered, including dose dosing schedule and treatment. Assessments to be made Other permitted and non-permitted medication How to monitor patient compliance How to assess efficacy How to assess safety including recordings and reporting adverse effects A description of the statistical methods to be employed The number of subjects plan to be enrolled Criteria for the termination of the trial

Answer 7

Disproportionate regulatory requirements high cost lack of harmonisation the following features have led to a significant decline in clinical trials in the EU. Thus it is being replaced with the new EU clinical trial regulation which aims to restore the use competitiveness in clinical research with a patient orientated research back to Europe.

Answer 8

That the study is important and cannot be answered with an existing evidence The investigators are properly qualifies Patients are safeguarded and their information is adequate comprehensible and appropriate Sufficient resource resources, staff and finances are available The benefits will outweigh the risk Usually include an independent data monitoring committee known as a data and safety monitoring board which assess if the study should be continued or stopped based on interim evaluations. This may be if the side effects are larger than unexpected.

Answer 9

This is a copy of all trial results positive and negative given to the European medicines evaluations agency EMA these have the ability to change the marketing authorisation for the drugs okay? Got to statistics

Answer 10

What is Standard Deviation? One standard deviation is calculated 68% of data point are expected to be within one standard deviation and 95% are expected to be within two Standard deviation (SD) is a measure of how spread out the values in a dataset are. It tells you how much the individual data points deviate from the mean (average) of the dataset. • A low standard deviation means the data points are close to the mean (less variability). • A high standard deviation means the data points are more spread out from the mean (more variability). How to Calculate Standard Deviation 1. Formula for Standard Deviation For a population (every possible data point is included): For a sample (a subset of data is used): Where: • = population standard deviation • = sample standard deviation • = each data point • = population mean • = sample mean • = total number of values in the population • = total number of values in the sample 2. Step-by-Step Calculation 1. Find the Mean (): Add all data points and divide by the number of values. 2. Subtract the Mean from Each Data Point: This finds the difference between each value and the mean. 3. Square Each Difference: Squaring removes negative values. 4. Find the Mean of Squared Differences: • For a population: Divide by (total number of values). • For a sample: Divide by (one less than the sample size). 5. Take the Square Root: This gives the standard deviation. Example Calculation Suppose you have these five values: 2, 4, 6, 8, 10 1. Mean: 2. Subtract the mean from each value: 3. Square each difference: 4. Find the mean of the squared differences: 5. Take the square root: Final Answer: Standard deviation = 2.83 This means that, on average, the data points are 2.83 units away from the mean.

Answer 11

Risk Ratio (Relative Risk) – Key Points • Definition: Measures how much more or less likely an event (e.g., disease) is in an exposed group compared to an unexposed group. • Interpretation: • RR > 1: Exposure increases risk of the outcome. • RR < 1: Exposure reduces risk (protective effect). • RR = 1: No difference in risk between groups. • How to Calculate: 1. Find the risk in the exposed group (cases ÷ total exposed). 2. Find the risk in the unexposed group (cases ÷ total unexposed). 3. Divide the exposed risk by the unexposed risk. • Example: If smokers have a 10% risk of lung cancer and non-smokers have a 2% risk: • Risk Ratio = 10% ÷ 2% = 5.0 • Smokers are 5 times more likely to develop lung cancer. • Used In: Cohort studies to compare risk between groups.

Answer 12

Absolute Risk Reduction (ARR) – Key Points • Definition: Measures the actual difference in risk between two groups (e.g., those who receive treatment vs. those who do not). It shows how much a treatment or intervention reduces risk in absolute terms. • Interpretation: • Higher ARR: The treatment is more effective at reducing risk. • Lower ARR: The treatment has little impact. • How to Calculate: 1. Find the risk in the untreated/control group (cases ÷ total in control). 2. Find the risk in the treated/intervention group (cases ÷ total in treatment). 3. Subtract the treated risk from the control risk. • Example: • In a study, 10% of patients without a vaccine get the flu. • Only 2% of vaccinated patients get the flu. • ARR = 10% - 2% = 8% • The vaccine reduces flu cases by 8 percentage points. • Used In: Clinical trials to measure the actual benefit of a treatment.

Answer 13

Relative Risk Reduction (RRR) – Key Points Essentially percentage change worked out with absolute risk reduction over control times 100 • Definition: Measures how much a treatment or intervention reduces risk relative to the original (untreated) risk. It shows the percentage reduction in risk due to the treatment. • Interpretation: • Higher RRR: The treatment is more effective at reducing risk. • Lower RRR: The treatment has less impact. • How to Calculate: 1. Find the absolute risk reduction (ARR) (risk in control group – risk in treatment group). 2. Divide ARR by the risk in the control group. 3. Multiply by 100 to express as a percentage. • Example: • Control group risk: 10% of patients without a vaccine get the flu. • Treatment group risk: 2% of vaccinated patients get the flu. • ARR = 10% - 2% = 8% • RRR = (8% ÷ 10%) × 100 = 80% • The vaccine reduces flu risk by 80% relative to the control group. • Used In: Clinical trials to compare the proportional benefit of treatments.

Answer 14

P-Value and Confidence Intervals – Key Points 1. P-Value • Definition: The probability of getting the observed results (or more extreme) if the null hypothesis is true. • Purpose: Helps determine whether an effect is statistically significant or just due to chance. • Threshold: Typically p < 0.05 is considered significant, meaning there is less than a 5% chance the result occurred by random variation. 2. Confidence Intervals (CI) • Definition: A range of values that is likely to contain the true population value with a given level of confidence (e.g., 95%). • Example: A 95% CI of 2.5 to 5.0 means we are 95% confident the true effect lies within this range. • Narrow CI: More precise estimate. • Wide CI: Less precise, more uncertainty. How They Are Related • A p-value < 0.05 suggests statistical significance, but a confidence interval gives more information by showing the range of possible values. • If a 95% CI does not include zero (for differences) or does not include 1 (for risk ratios), the result is statistically significant (p < 0.05). • CI helps understand the magnitude and reliability of an effect, while p-values only indicate significance. Example A study shows a new drug reduces blood pressure by 4 mmHg with: • p = 0.03 → Statistically significant. • 95% CI: 1.2 to 6.8 mmHg → The true effect is likely between 1.2 and 6.8 mmHg. • Since zero is not in the CI, the effect is likely real (p < 0.05). Takeaway: • Use p-values for significance (yes/no). • Use confidence intervals for precision and effect size (how big and reliable the effect is).

Answer 15

Number Needed to Treat (NNT) – Key Points • Definition: The number of patients who need to receive a treatment for one additional person to benefit compared to a control. • Purpose: Helps assess how effective a treatment is in practical terms. How to Calculate NNT 1. Find the Absolute Risk Reduction (ARR) (risk in control group – risk in treatment group). 2. Calculate NNT: (Use ARR as a decimal, not a percentage.) Example • A new drug reduces heart attack risk from 10% (control group) to 5% (treatment group). • ARR = 10% - 5% = 5% (or 0.05 as a decimal). • NNT = 1 / 0.05 = 20. Interpretation • NNT = 20 → You need to treat 20 people for one extra person to benefit. • Lower NNT = More effective treatment (e.g., NNT of 2 means treatment is very effective). • Higher NNT = Less effective treatment (e.g., NNT of 100 means limited benefit). Key Takeaways • Used in clinical trials to evaluate treatment impact. • Helps compare treatments to see which is more beneficial. • A lower NNT is better, but it must be balanced with risks and side effects.

Answer 16

Level of significance which is usually 0.0 5AP value of lesson 0.05 means that there is less than a 5% chance of incorrectly reporting a positive effect known as a type one error Power of the study when there is a difference will we be able to detect it? This is a Type II error and is usually set at 80% however sometimes 90 Expected effect of intervention or effect size involves making an estimate of how much difference the interval makes usually unlimited information a drug expected to have or shown a large effect may require smaller sample however the one with a smaller effect may require larger sample size Be expected degree of variability or standard deviation if you’re measuring a stock which is very variable you’ll need more people rather than a stat that is more tightly bound

Answer 17

This is a clinical trial where there is a specified end point based on events and a certain level of statistical data being hit instead of planning out and attempting to reach the amount of data to become significant for example the trial ends 100 people have had a heart attack

Answer 18

This is a study where two medicines are being conferred but just to make sure that the new one is no worse than the other although the new one may have better dosing schedule for example or alternative benefits Boundaries for non-inferiority are set beforehand and are accepted by regular two bodies such as the European medicines agency The accepted difference is generally smaller than the treatment benefit found in the placebo controlled superiority trials and the sample size required is usually bigger than those for superiority trials

Answer 19

Intention to treat an ITT analysis is used this is where all randomise patients in the medicine group which regardless of the treatment they actually received there with draw and deviation from protocol counted. This does introduce an increased risk for type two errors. An alternative way to do this is ITT analysis with last observed carried forward with the last available measurement prior to the withdrawal is retained analysis Alternatively MITT which allows the exclusion of randomise subjects in a justified way for example they never started treatment Per protocol is an alternative form which is only performed on patients who have completed treatment specified in protocol Superiority trial is made by ITT although non-inferiority is both ITT and per protocol

Answer 20

Dominant Inheritance • One mutated gene from one parent causes disease. • 50% chance of passing to children. • Seen in every generation. • Examples: Huntington’s, Marfan syndrome. Autosomal Recessive Inheritance • Two mutated genes (one from each parent) needed for disease. • 25% chance of affected child if both parents are carriers. • May skip generations. • Examples: Cystic fibrosis, Sickle cell anemia.

Answer 21

X-Linked Recessive • More common in males (who have only one X chromosome). • Females can be carriers (one faulty X) or affected (if both X chromosomes carry the mutation, which is rare). • Example diseases: Hemophilia, Duchenne muscular dystrophy, Red-green color blindness. • Inheritance pattern: • Affected fathers cannot pass it to sons (sons inherit Y from the father). • Carrier mothers have a 50% chance of passing it to sons (who will be affected) and a 50% chance of passing it to daughters (who will be carriers). 2. X-Linked Dominant • Affects both males and females, but females may have milder symptoms due to X-inactivation. • Example diseases: Rett syndrome, Fragile X syndrome. • Inheritance pattern: • Affected fathers pass it only to daughters (who inherit his X). • Affected mothers have a 50% chance of passing it to both sons and daughters. Key Points: • Males are more vulnerable to X-linked recessive conditions. • Fathers cannot pass X-linked traits to their sons. • X-inactivation in females can lead to variable expression of symptoms.

Answer 22

This is when the gene on the Y chromosome is affected such as Y chromosome infertility which will affect all sons as they only get the Y chromosome from their father

Answer 23

Two different versions of alleles that are both expressed and both make slightly different protein example is ABO the group

Answer 24

This is sometimes referred to his maternal inheritance as only females can pass mutations in the mitochondrial DNA to children while males can be affected. They cannot pass this on.

Answer 25

Reduced Penetrance – Key Points • Definition: When a person inherits a disease-causing mutation but does not show symptoms or has milder symptoms than expected. • Penetrance: The percentage of people with the mutation who actually develop the disease. • Complete penetrance = 100% (everyone with the mutation shows symptoms). • Reduced penetrance = Less than 100% (some people with the mutation do not show symptoms). Example • BRCA1 mutation: Increases breast cancer risk, but not all carriers develop cancer (penetrance is incomplete). • Huntington’s disease: Has high penetrance, meaning most people with the mutation will develop symptoms. Why Does It Happen? • Other genes may modify disease expression. • Environmental factors can influence symptom development. • Random chance—some people may never show signs despite having the mutation. Key Takeaway Reduced penetrance means having the gene does not always mean developing the disease.