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BACKGROUND: Hereditary angioedema (HAE) is caused by low levels of or defects in C1 inhibitor. Although disease activity may be modified by prophylaxis, emergency treatment, treatment for comorbidities, and oral contraceptives, the extent of their use is unclear. OBJECTIVE: To investigate trends in the use of disease-specific and interfering drugs in patients with HAE compared with the general population in Sweden. METHODS: In a nationwide, longitudinal study, 239 patients with HAE and 2 383 controls were compared with the Prescribed Drug Register (2005e2019). These data reflect rates of dispensed prescriptions from pharmacies in Sweden. RESULTS: Attenuated androgens were used by approximately 10% of patients with HAE. The number of individuals treated with prophylactic plasma-derived C1 inhibitor increased during this period to reach almost 25% in men and 35% in women in 2019. Tranexamic acid was prescribed to 5% to 15% of patients, primarily children and young adults. Rates of prescriptions for icatibant, an emergency medication, showed a steady increase since its introduction in 2010, in particular among middle-aged women, suggesting poorly controlled disease. The use of di-uretics, calcium channel blockers, and gestagens was more common in patients with HAE than in controls, whereas angiotensin-converting enzyme inhibitors were rarely collected. CONCLUSIONS: Despite concerns regarding side effects, approximately 10% of patients with HAE received attenuated androgens for long-term prophylaxis. The common use of emergency medication also suggests poorly controlled disease in many patients, highlighting the need for increased focus on prophylactic treatment.

A dynamic epithelium and a rich microbiota, separated by multi-layered mucus, make up the complex colonic cellular environment. Both cellular systems are characterized by high inter-and intraindividual differences, but their impact on drug distribution and efficacy remains incompletely understood. This research gap is pressing, as, e.g., inflammatory disorders of the colon are on the rise globally. In an effort to help close this gap, we provide considerations on determining colonic epithelial and microbial cellular parameters, and their impact on drug bioavailability. First, we cover the major cell types found in vivo within the epithelium and microbiota, and discuss how they can be modeled in vitro. We then draw attention to their structural similarities and differences with regard to determinants of drug distribution. Once a drug is solubilized in the luminal fluids, there are two main classes of such determinants: 1) binding processes, and 2) transporters and drug-metabolizing enzymes. Binding lowers the unbound intracellular fraction (fu,cell), which will, in turn, limit the amount of drug available for transport to desired sites. Transporters and drug metabolizing enzymes are ADME proteins impacting intracellular accumulation (Kp). Across cell types, we point out which processes are likely particularly impactful. Together, fu,cell and Kp can be used to describe intracellular bioavailability (Fic), which is a measure of local drug distribution, with consequences for efficacy. Determining these cellular parameters will be beneficial in un-derstanding colonic drug distribution and will advance the field of drug delivery.

A new modelling approach for dissolution of polydisperse powders is developed within the framework of the classical Noyes-Whitney/Nernst-Brunner analysis. Its distinguishing feature is that the underlying continuous particle-size distribution is retained. Two different but related dependencies of the diffusion-layer thickness on particle size are considered. First, a power-law dependence that interpolates between a thickness that is proportional to (or equals) the particle radius (obtained when the exponent equals 1) and a constant thickness (obtained when the exponent is 0). Second, a piecewise linear function such that the thickness equals the particle radius for sufficiently small particles and is constant for larger ones. The modelling approach is exemplified by consideration of a lognormal particle-size distribution. Highly accurate closed-form expressions for the fraction of dissolved drug are obtained for dissolution under sink conditions (which are exact if the diffusion-layer thickness is radius-independent). Moreover, it is demonstrated that any result derived under sink conditions can be reused to determine the fraction of dissolved/absorbed drug under non-sink conditions, using the concept of a retarded time. Comparison with literature data and experiments are used to validate the modelling approach and to demonstrate its usefulness in a practical context.

Background: Multi-dose drug dispensing (MDD) is an alternative to assist patients with difficulties in administering and handling their medications. In 2019 the primary care units at Region Gotland reported a high number of discrepancies, regarding patients with MDD discharged from the Hospital of Visby. Due to the high proportion of discrepancies between the patient's medication list in TakeCare and the prescription list of MDD the clinical pharmacists at the hospital began to check all patients marked for discharge in order to discover and prevent eventual discrepancies. Aim: To identify discrepancies between the patient’s medication list and the prescription for MDD when discharged from the Hospital of Visby and investigate whether there has been a decrease since 2019. Method: A quantitative cross-sectional study was performed. Medication lists from each patient’s journal and their prescribing record from the prescription system for MDD were reviewed to identify discrepancies, which then were noted and discussed with the physician in charge. Identified discrepancies were rated into pre-defined categories and compared with data from previous years. A chi-square test was performed to investigate the significant difference of discrepancies between the units. The results from the intervention were summarized into figures and tables. Results: Medication lists from 144 patients with a mean age of 83 years were included. Discrepancies were identified in 34% of the patients and a total of 98 discrepancies were noted, which proves a significant decrease since 2019 when the number of discrepancies was 70%. Totally 79% of the discrepancies were estimated to have occurred during the patient's hospital stay. The highest number of discrepancies were found in the medical department and the difference between all inpatient care departments was significant (p <0.0001). Conclusion: The results indicate a decrease in discrepancies since 2019. Further research is necessary to cla

When drugs need to be delivered to the respiratory system dry powder inhalers (DPIs) are often used. The powders in DPIs often consists of a micronized active pharmaceutical ingredient (API) that is adhered to a larger carrier particle forming an adhesive mixture. To achieve a good drug delivery aerosolization is very important and to improve the aerosolization a force control agent such as magnesium stearate (MgSt) may be used. The aim of this project is to investigate how MgSt effects the aerosolization and bulk properties of adhesive mixtures containing different amount of API. Several analyses of bulk properties such as density, bulk density and compressibility were made. The results from these experiments showed that the only bulk properties that had a significant change when MgSt was added was the bulk density. When investigating if the aerosolization properties changed with added MgSt a fast-screening impactor (FSI) and a next generation impactor (NGI) were used. The results showed a clear improvement of aerosolization properties for all the powder containing MgSt. The fine particle fraction (FPF) and fine particle dose (FPD) both increased for all the powder when MgSt was added. The pressure drop sensitivity decreased when MgSt was added which also was desired. In conclusion adding MgSt seems to be beneficial for the aerosolization properties regardless of the amount of API in the powder.

Background: There are some health care centers in Region Västmanland that always turn a profit, and other health care centers which always go at a loss. Aim: The aim of this study was to analyze the potential reasons as to why the same health care centers always profit, and the other health care centers always go at a loss under year 2022. Methods: A cross-sectional study with register data for the year 2022 was used as a method. The analysis was performed by aggregating different indicators and measures. For example, the age and sex of the patients, socioeconomic status, morbidity, and number of listed patients that the health centers have. Two different therapy areas were chosen for deeper analysis - diabetes and atrial fibrillation. Medicines for these diagnoses have the highest cost for the health centers. In addition to this, differences between the health care centers in prescribing of over-the-counter medicines and in selection of generic drugs were also considered. Results: The results show that the three health centers that lost the most had 29 percent higher costs per diabetes patient of the more expensive diabetes drugs compared to other three health centers that always make a profit. The health centers that had the largest loss had higher costs of Lyrica, a more expensive drug compared to other bioequivalent drugs, than the other health centers. The health centers that lost the most had older patients, and more patients who were socioeconomically disadvantaged. Two of the health centers that lost the most had higher CNI scores, which means that the patients at these health centers had a lower socio-economic status. In conclusion, the health care centers that lost the most had the highest diabetes costs, especially from the more expensive drugs and they had also more older patients.

Background: A negative outcome of consuming and manufacturing pharmaceuticals is that these substances reach the environment through different pathways. This can lead to severe consequences such as antibiotic resistance, but also disturbances in entire ecosystems. Educating health care professionals such as doctors and pharmacists about the subject could contribute to more environmentally friendly, pharmaceutical-related decisionsto be taken in the future, resulting in less negative environmental impacts. Aim: To describe Swedish universities' educations of medical and pharmacy programs regarding the impact of pharmaceuticals on the environment, as well as how the students in their future professional role can contribute to reduce this impact. Method: A survey study consisting of two parts. One questionnaire-based part, and one part reviewing educational plans for pharmacy and medical programs. One questionnaire was sent to course managers for courses within pharmacy programs, and one to program managers for the medical programs. Results: In total, 47 out of 100 course managers and 6 out of 7 program managers participated in the questionnaires. 19 course managers indicated that their courses within pharmacy programs contain education about the environmental impacts of pharmaceuticals. All 6 program managers indicated that their program contains education about this. The most common areas educated about were sustainable drug use, sustainable drug manufacturing and development. All education plans contained learning objectives related to the environmental impacts of pharmaceuticals. Conclusion: Sweden’s pharmacy and medical programs do contain some education about the environmental impacts of pharmaceuticals. However, more education is needed, especially regarding knowledge databases.

The gold standard for pharmacometrics modeling, along with its modeling format, is currently NONMEM. In order to use other software, there is often a manual step of converting a model from one format to another, which is both time-consuming and causes manual errors. This project aimed to solve this problem by creating a conversion- and validation tool from NONMEM to two formats: nlmixr2 and RxODE2. These are both, unlike NONMEM, freely available and integrated into R. This was done by integrating the two tools (conversion and validation) into the program Pharmpy, which can extract model information from NONMEM's model format. For conversion, the model was read into Pharmpy and then, part by part, converted to the respective model format. The associated validation compared the predictions of the respective programs to see if they differed significantly from each other. The project showed that this type of conversion is possible, but the programs showed a greater difference than expected. Part of this can be explained by a rounding of parameter values in Pharmpy, but further analysis also indicated fundamental differences in the determination of the predictions between the programs. Larger differences in predictions are for instance oftentimes equidistant from the actual observation, meaning the predictions are presumably calculated differently. While not disproving the converted model, smaller discrepancies between the programs would indicate a more confident validation. In summary, the developed tools are considered useful for models where Pharmpy supports parsing of the model. If not for complete conversion, then at least for partial conversion with manual correction, which is also an improvement over an entirely manual workflow.

Gender differences in drug use in Sweden – a systematic analysis of changes taking place during a decade Background: From a global perspective, Sweden upholds a high-quality healthcare provided on equal terms. Despite this, there are differences in health and living conditions as well as drug utilization between men and women. Aim: The aim of this study was to analyze how gender differences in drug use in Sweden have changed over the past 10 years. Specifically, to observe within which pharmacological groups large increases and decreases have taken place between 2011 and 2021. Method: A quantitative cross-sectional study was conducted to compare the prevalence of drug use between women and men in 2011 and 2021. The study used data from the Swedish Prescribed drug register containing information about all dispensed prescription drugs. Results: The gender differences differ depending on whether the differences are analyzed in relative or absolute terms. The largest sex difference in absolute numbers was antibiotics with a greater use were in women, while lipid lowering agents were showed the highest use among males. The largest increase in relative gender difference from 2011 to 2021 was for antimigrane preparations while the relative gender differences has decreased most substantially for mineral substances. Conclusion: The study shows that gender differences still exist and have not decreased in the last 10 years. Some findings on gender differences could be explained using research on prevalence of diseases between the sexes, while some differences could not be justified using medical explanations. Unexplainable gender differences can be explained by normative structures that exist and affect healthcare in Swedish society.

Aproximatly 1-4 % of the world population suffers from bipolar disorder that is classified as one of the main causes of disability, but despite this no pathophysiological cause is known. A bipolar disorder is characterized by periods of depressive and manic episodes with classification as type-1 and type-2 depending on the main symptoms. Depressive episodes display as unipolar depression whilst manic episodes appear as reduced need of sleep, excessive selfesteem and rushed speech that in some cases is followed by psychosis. Unfortunately, bipolar disorder can be seen as connected to a higher rate of suicide at a 10-30 times higher risk in comparison to the general population and the treatment is failing to fulfill requirements. Lithium is frequently used as maintenance treatment but is linked to complicated side effects such as hypothyreosis and weight gain. The treatment can also result in positive secondary effects such as the alleged anti-suicidal effect. The aim of this study was to describe the anti-suicidal effects of lithium treatment in patients suffering from bipolar disorder and illustrate how different study methods affect the results. This study was based on clinical trials, register-based studies and one review-article where the Pubmed database was used to search for articles. The result was that three out of six studies could demonstrate anti-suicidal effects of lithium when compared to other treatments and placebo. These three studies were made on a bigger population and went on for many years. The conclusion is that the ability to show the anti-suicidal effects of lithium varied and so did the methods used in the studies. There was a trending aspect that showed great success of lithium regarding the anti-suicidal effects amongst studies that went on for many years and was based on a bigger population but in lack of power, this study can not attest to lithiums anti-suicidal effects.

Background: Pharmaceuticals are a big part of healthcare expenditures. Advancements such as the sequencing of the human genome and technical methods has led to the development of more advanced drugs. Aim: The aim of this study was to explore the trends in new drug development areas and the costs of drugs in different therapy areas. Method: To do this, data from the Swedish Medical Products Agency, e-Hälsomyndigheten and the 20 biggest pharmaceutical companies regarding new approved drugs during a 20-year period, costs and new chemical entities in late development stage has been analyzed. Results: Each year, between 20 and 60 new drugs are approved. New chemical entities are most prevalent in the ATC-group L, which includes oncology and immunomodulating drugs. Innovation is also seen in group J, antiinfectives. The cost of drugs has increased during the study period, especially for oncology drugs. In the coming years, we can expect the introduction of even more oncology drugs, as mostdrugs in later development phases are expected to be classified in this group. Conclusion: Over the studied period, the most innovative therapeutic group has not changed but rather grown. The cost of drugs has also grown, possibly because of more new drugs introduced but also due to expanded indications and larger patient groups. It is hard to see a future where oncology drugs are not the biggest cost since in the coming years, many of the expected new drugs will fall into the same category.

Humant immunbristvirus (HIV) tillhör gruppen retrovirus. Det finns två typer av HIV, HIV-1 och HIV-2. HIV-1 är den mest spridda typen. Viruset angriper CD4+ T-hjälparceller och använder cellerna för att replikera. När HIV förökar sig minskar antalet CD4+ T-hjälparceller vilket leder till nedsatt immunförsvar och kroppen får svårare att hantera andra infektioner. Obehandlad HIV kan leda till ”acquired immunodeficiency syndrome” (AIDS) som innebär att immunförsvaret är kraftigt nedsatt och kroppen därmed är mycket känslig mot alla sorters infektioner. Globalt uppskattas cirka 38,4 miljoner människor leva med HIV, och 40 miljoner människor har avlidit på grund av AIDS. Det finns ingen botande behandling mot HIV, men flera olika behandlingsmöjligheter för att minska virusmängden i kroppen. HIV muterar dock frekvent vilket innebär att viruset kan utveckla resistens mot läkemedel. För att minska risken för resistensutveckling behandlas HIV med kombinationsbehandling där läkemedel med olika verkningsmekanism kombineras. Standardbehandlingen mot HIV har under en lång period varit en kombination av tre eller fler olika läkemedel. Det finns dock nackdelar med att kombinera tre eller flera olika läkemedel, till exempel läkemedel-läkemedelsinteraktioner och ökad frekvens av biverkningar. På grund av detta testas nu i olika studier om kombinationer med endast två läkemedel kan fungera lika bra. Syftet med det här arbetet var att genomföra en litteraturstudie för att beskriva effekt och säkerhet av kombinationsbehandling mot HIV-1 med två antiretrovirala läkemedel där det ena läkemedlet var integrashämmaren dolutegravir, jämfört med tidigare godkända kombinationsbehandlingar med tre eller fyra antiretrovirala läkemedel. Dolutegravir valdes på grund av att läkemedlet har hög resistensbarriär och ingår i två rekommenderade kombinationer med två läkemedel. För att svara på syftet genomfördes sökningar efter relevanta artiklar i PubMed. Artiklarna som inkluderades skulle vara rando, Human immunodeficiency virus (HIV) belongs to the group of retroviruses. There are two types of HIV, HIV-1 and HIV-2. HIV-1 is the most widespread type. The virus attacks CD4+ helper T cells and uses the cells to replicate. When HIV replicates, the number of CD4+ helper T cells decreases, which leads to a weakened immune system which makes it harder for the body to fight other infections. Untreated HIV can lead to acquired immunodeficiency syndrome (AIDS), which means that the immune system is severely weakened, and the body is, therefore, very susceptible to many kinds of infections. Globally, it is estimated that about 38,4 million people are living with HIV, and 40 million people have died due to AIDS. There are no cure for HIV, but several different treatment options to reduce the viral load in the body. HIV has a high frequency of mutations which can make the virus resistant to a drug. To reduce the risk of resistance, HIV is normally treated with a combination of drugs with different mechanisms of action. The standard treatment for HIV has for a long time been a combination of three or more different drugs. However, there are disadvantages to combining several different drugs, such as drug-drug interactions and increased risk of side effects. Because of this, recent studies have been testing whether combinations with only two drugs can work just as well. The purpose of this study was to review the efficacy and safety of combination therapy for HIV-1 with two antiretroviral drugs, where one drug was the integrase inhibitor dolutegravir, compared to previously approved combination therapies with three or four antiretroviral drugs. Dolutegravir was chosen due to the drug's high resistance barrier and inclusion in two recommended two drug regimens. To answer the purpose, searches for relevant articles were conducted on PubMed. The articles that were included were randomized controlled trials with a non-inferiority study design, while articles that presented secon

Malignt melanom är den allvarligaste formen av hudcancer och orsakas av att friska melanocyter börjar dela sig okontrollerat, vilket resulterar i en tumör. Det finns flera riskfaktorer för melanom men en av de främsta är exponering av UV-strålning. En ytterligare riskfaktor för malignt melanom är olika genmutationer varav av en vanligt förekommande genmutation är BRAF-mutation. Det finns flera behandlingsmetoder men en nyare behandling som används vid de senare stadierna av melanom är immunterapi. Programmed cell death 1 (PD-1)-hämmaren nivolumab och cytotoxic T-lymphocyte antigen 4 (CTLA-4)-hämmaren ipilimumab är två checkpointhämmare som på olika sätt hämmar tumörtillväxten. Syftet med denna litteraturstudie var att undersöka nivolumab och ipilimumabs effekt samt säkerhet både som monoterapi och kombinationsterapi. Databasen PubMed användes för att välja ut fem RCT-studier. Vid sökningen användes sökord som ”melanoma”, ”nivolumab” och ”ipilimumab”. Några av inklusionskriterierna var att patienterna hade melanom i stadie III och IV, och både patienter med BRAF V600-mutation och med BRAF wild-type inkluderades. Ett av exklusionskriterierna var artiklar som var inriktade på melanom i hjärna, lunga eller ögon. Resultatet visade att nivolumab och ipilimumab som kombinationsterapi var mer effektiv avseende både total överlevnad och progressionsfri överlevnad jämfört med nivolumab och ipilimumab som monoterapi. Nivolumab som monoterapi var mer effektiv än vad ipilimumab som monoterapi var avseende total överlevnad och progressionsfri överlevnad. Behandlingen med nivolumab och ipilimumab som kombinationsterapi resulterade däremot i fler biverkningar jämfört med nivolumab och ipilimumab som monoterapi. Patienter som behandlades med nivolumab som monoterapi upplevde färre biverkningar än vad patienterna som behandlades med ipilimumab som monoterapi upplevde. Utifrån resultaten i de studier som granskats så är slutsatsen att kombinationsbehandlingen var den mest effektiva

Hypertoni är en riskfaktor för allvarliga kardiovaskulära sjukdomar. Olika läkemedelsklasser används vid behandling av hypertoni. Dessa inkluderar angiotensin omvandlade enzymhämmare, angiotensin II-receptorblockerare, kalciumkanalblockerare och tiaziddiuretika. Även om nuvarande läkemedelsterapier kan vara effektiva, är det få som kan uppnå målblodtryck. De flesta patienter med hypertoni kräver minst två antihypertensiva läkemedel för att uppnå sitt målblodtryck. Detta ledde till komplicerade behandlingsmetoder som i sin tur har blivit en stor bidragande faktor till dålig patientföljsamhet. Även om ett stort antal läkemedel finns tillgängliga för behandling, är kontrollen av blodtryck dålig på grund av patienternas dåliga följsamhet till medicinering som vanligtvis är en kombination av flera substanser. Följsamheten minskar med antalet tabletter som en patient behöver ta vilket leder till en komplicerad behandlingsstrategi. Syftet med detta examensarbete var att undersöka blodtryckssänkande effekt med en enkel tablettform Single-Pill Combination (SPC) som innehåller en kombination av flera antihypertensiva läkemedelsklasser och att undersöka patienternas följsamhet till (SPC) behandling. Metod det här arbetet är en litteraturstudie utförd i PubMed. Olika sökord användes” single-pill combination in hypertension”, “Fixed dose combination in hypertension “, “Adherence to single-pill combination in hypertension”. Sökningen filtrerades till “Randomized controlled trial”. Nya studier valdes ut som undersökte effekten av SPC och följsamhet till behandling. Resultat Studier 1,2,3 och 4 som undersökte effekten gav positiva resultat som gynnade SPC framför standardmonoterapi och placebo. SPC kunde minska blodtrycket statiskt signifikant i alla studierna. I studie 1 blev den genomsnittliga skillnaden i SBT mellan grupperna (–6,9) mm Hg med (p-värde <0,001). I studie 2 blev skillnaden i genomsnittlig 24-timmars SBT mellan SPC- och placeboperioder (–18,7) mm Hg med p-värde, Background Hypertension is a risk factor for serious cardiovascular diseases. Different drug classes are used in the treatment of hypertension. These include angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, calcium channel blockers, and thiazide diuretics. Although current drug therapies can be effective, few are able to achieve target blood pressure therefore it has become well-known that most hypertensive patients require at least two antihypertensive drugs to reach their target blood pressure. This led to complicated treatment methods, which in turn has become a significant contributing factor to poor patient compliance. When two or more drug classes are combined, this contributes to improved efficacy, as different mechanisms of action work together to block different pathways to high blood pressure. This leads to lower doses of the individual components being used, which results in a reduced likelihood of side effects. Although a large number of drugs are available for treatment, there is still poor control of blood pressure due to patients' poor adherence to medication, which is usually a combination of several substances. Adherence decreases with the number of tablets a patient needs to take, leading to a complicated treatment strategy. Lower levels of adherence are associated with poorer blood pressure control. Aim The aim of the work is to investigate the blood pressure-lowering effect with a simple tablet form "Single-Pill Combination" (SPC) that contains a combination of several antihypertensive drug classes and to investigate the patients' adherence to this form of treatment (SPC). Method This work is a literature study carried out in Pubmed. Different search terms were used: "single-pill combination for the treatment of hypertension", "Fixed dose combination in hypertension", and "Adherence to single-pill combination for hypertension". The search was filtered to "Randomized controlled trial". New studies were selected that inve

Our skin constitutes an effective permeability barrier that protects the body from exogenous substances but concomitantly severely limits the number of pharmaceutical drugs that can be delivered transdermally. In topical formulation design, chemical permeation enhancers (PEs) are used to increase drug skin permeability. In vitro skin permeability experiments can measure net effects of PEs on transdermal drug transport, but they cannot explain the molecular mechanisms of interactions between drugs, permeation enhancers, and skin structure, which limits the possibility to rationally design better new drug formulations. Here we investigate the effect of the PEs water, lauric acid, geraniol, stearic acid, thymol, ethanol, oleic acid, and eucalyptol on the transdermal transport of metronidazole, caffeine, and naproxen. We use atomistic molecular dynamics (MD) simulations in combination with developed molecular models to calculate the free energy difference between 11 PE-containing formulations and the skin’s barrier structure. We then utilize the results to calculate the final concentration of PEs in skin. We obtain an RMSE of 0.58 log units for calculated partition coefficients from water into the barrier structure. We then use the modified PE-containing barrier structure to calculate the PEs’ permeability enhancement ratios (ERs) on transdermal metronidazole, caffeine, and naproxen transport and compare with the results obtained from in vitro experiments. We show that MD simulations are able to reproduce rankings based on ERs. However, strict quantitative correlation with experimental data needs further refinement, which is complicated by significant deviations between different measurements. Finally, we propose a model for how to use calculations of the potential of mean force of drugs across the skin’s barrier structure in a topical formulation design.

The main focus of this thesis has been on Quantitative Structure Activity Relationship (QSAR) modeling using methods producing valid measures of uncertainty. The goal of QSAR is to prospectively predict the outcome from assays, such as ADMET (Absorption, Distribution, Metabolism, Excretion), toxicity and on- and off-target interactions, for novel compounds. QSAR modeling offers an appealing alternative to laboratory work, which is both costly and time-consuming, and can be applied earlier in the development process as candidate drugs can be tested in silico without requiring to synthesize them first. A common theme across the presented papers is the application of conformal and probabilistic prediction models, which are used in order to associate predictions with a level of their reliability – a desirable property that is essential in the stage of decision making. In Paper I we studied approaches on how to utilize biological assay data from legacy systems, in order to improve predictive models. This is otherwise problematic since mixing data from separate systems will cause issues for most machine learning algorithms. We demonstrated that old data could be used to augment the proper training set of a conformal predictor to yield more efficient predictions while preserving model calibration. In Paper II we studied a new approach of predicting metabolic transformations of small molecules based on transformations encoded in SMIRKS format. In this work use used the probabilistic Cross-Venn-ABERS predictor which overall worked well, but had difficulty in modeling the minority class of imbalanced datasets. In Paper III we studied metabolomics data from patients diagnosed with Multiple Sclerosis and found a set of 15 discriminatory metabolites that could be used to classify patients from a validation cohort into one of two sub types of the disease with high accuracy. We further demonstrated that conformal prediction could be useful for tracking the progression of the disea

Background Suboptimal exposure to antituberculosis (anti-TB) drugs has been associated with unfavourable treatment outcomes. We aimed to investigate estimates and determinants of first-line anti-TB drug pharmacokinetics in children and adolescents at a global level. Methods We systematically searched MEDLINE, Embase and Web of Science (1990–2021) for pharmacokinetic studies of first-line anti-TB drugs in children and adolescents. Individual patient data were obtained from authors of eligible studies. Summary estimates of total/extrapolated area under the plasma concentration–time curve from 0 to 24 h post-dose (AUC0–24) and peak plasma concentration (Cmax) were assessed with random-effects models, normalised with current World Health Organization-recommended paediatric doses. Determinants of AUC0–24 and Cmax were assessed with linear mixed-effects models. Results Of 55 eligible studies, individual patient data were available for 39 (71%), including 1628 participants from 12 countries. Geometric means of steady-state AUC0–24 were summarised for isoniazid (18.7 (95% CI 15.5–22.6) h·mg·L−1), rifampicin (34.4 (95% CI 29.4–40.3) h·mg·L−1), pyrazinamide (375.0 (95% CI 339.9–413.7) h·mg·L−1) and ethambutol (8.0 (95% CI 6.4–10.0) h·mg·L−1). Our multivariate models indicated that younger age (especially <2 years) and HIV-positive status were associated with lower AUC0–24 for all first-line anti-TB drugs, while severe malnutrition was associated with lower AUC0–24 for isoniazid and pyrazinamide. N-acetyltransferase 2 rapid acetylators had lower isoniazid AUC0–24 and slow acetylators had higher isoniazid AUC0–24 than intermediate acetylators. Determinants of Cmax were generally similar to those for AUC0–24. Conclusions This study provides the most comprehensive estimates of plasma exposures to first-line anti-TB drugs in children and adolescents. Key determinants of drug exposures were identified. These may be relevant for population-specific dose adjustment or individualis

The pharmacokinetics (PK) of ethanol are important in pharmacology and therapeutics because of potential drug-alcohol interactions as well as in forensic science when alcohol-related crimes are investigated. The PK of ethanol have been extensively studied since the 1930s, although some issues remain unresolved, such as the significance of first-pass metabolism, whether zero-order kinetics apply, and the effects of food on bioavailability. We took advantage of nonlinear mixed-effects modeling to describe blood-alcohol concentration (BAC) profiles derived from 3 published clinical studies involving oral, intraduodenal, and intravenous administration of ethanol with and without food. The overall data set included 1510 BACs derived from 72 healthy subjects (60 men, 12 women) aged between 20 and 60 years. Two-compartment models with first-order absorption and Michaelis-Menten elimination kinetics adequately described the BAC profiles. Food intake had 2 separate effects: It reduced the absorption rate constant and accelerated the maximum elimination rate. Estimates of the maximum elimination rate (fasted) and the food effect (as a factor) were 6.31 g/h (95%CI, 6.04-6.59 g/h) and 1.39-fold (95%CI, 1.33-1.46-fold), respectively. Simulations showed that the area under the BAC-time curve (AUC) was smaller with lower input rate of ethanol, irrespective of any first-pass metabolism. The AUC from time 0 to 10 hours for a 75-kg subject was 2.34 g center dot h/L (fed) and 3.83 g center dot h/L (fasted) after an oral dose of 45 g ethanol. This difference was mainly attributable to the food effect on ethanol elimination and depended less on the absorption rate. Our new approach to explain the complex human PK of ethanol may help when BAC predictions are made in clinical pharmacology and forensic medicine.

Background: There are some health care centers in Region Västmanland that always turn a profit, and other health care centers which always go at a loss. Aim: The aim of this study was to analyze the potential reasons as to why the same health care centers always profit, and the other health care centers always go at a loss under year 2022. Methods: A cross-sectional study with register data for the year 2022 was used as a method. The analysis was performed by aggregating different indicators and measures. For example, the age and sex of the patients, socioeconomic status, morbidity, and number of listed patients that the health centers have. Two different therapy areas were chosen for deeper analysis - diabetes and atrial fibrillation. Medicines for these diagnoses have the highest cost for the health centers. In addition to this, differences between the health care centers in prescribing of over-the-counter medicines and in selection of generic drugs were also considered. Results: The results show that the three health centers that lost the most had 29 percent higher costs per diabetes patient of the more expensive diabetes drugs compared to other three health centers that always make a profit. The health centers that had the largest loss had higher costs of Lyrica, a more expensive drug compared to other bioequivalent drugs, than the other health centers. The health centers that lost the most had older patients, and more patients who were socioeconomically disadvantaged. Two of the health centers that lost the most had higher CNI scores, which means that the patients at these health centers had a lower socio-economic status. In conclusion, the health care centers that lost the most had the highest diabetes costs, especially from the more expensive drugs and they had also more older patients.

When drugs need to be delivered to the respiratory system dry powder inhalers (DPIs) are often used. The powders in DPIs often consists of a micronized active pharmaceutical ingredient (API) that is adhered to a larger carrier particle forming an adhesive mixture. To achieve a good drug delivery aerosolization is very important and to improve the aerosolization a force control agent such as magnesium stearate (MgSt) may be used. The aim of this project is to investigate how MgSt effects the aerosolization and bulk properties of adhesive mixtures containing different amount of API. Several analyses of bulk properties such as density, bulk density and compressibility were made. The results from these experiments showed that the only bulk properties that had a significant change when MgSt was added was the bulk density. When investigating if the aerosolization properties changed with added MgSt a fast-screening impactor (FSI) and a next generation impactor (NGI) were used. The results showed a clear improvement of aerosolization properties for all the powder containing MgSt. The fine particle fraction (FPF) and fine particle dose (FPD) both increased for all the powder when MgSt was added. The pressure drop sensitivity decreased when MgSt was added which also was desired. In conclusion adding MgSt seems to be beneficial for the aerosolization properties regardless of the amount of API in the powder.

Background: Multi-dose drug dispensing (MDD) is an alternative to assist patients with difficulties in administering and handling their medications. In 2019 the primary care units at Region Gotland reported a high number of discrepancies, regarding patients with MDD discharged from the Hospital of Visby. Due to the high proportion of discrepancies between the patient's medication list in TakeCare and the prescription list of MDD the clinical pharmacists at the hospital began to check all patients marked for discharge in order to discover and prevent eventual discrepancies. Aim: To identify discrepancies between the patient’s medication list and the prescription for MDD when discharged from the Hospital of Visby and investigate whether there has been a decrease since 2019. Method: A quantitative cross-sectional study was performed. Medication lists from each patient’s journal and their prescribing record from the prescription system for MDD were reviewed to identify discrepancies, which then were noted and discussed with the physician in charge. Identified discrepancies were rated into pre-defined categories and compared with data from previous years. A chi-square test was performed to investigate the significant difference of discrepancies between the units. The results from the intervention were summarized into figures and tables. Results: Medication lists from 144 patients with a mean age of 83 years were included. Discrepancies were identified in 34% of the patients and a total of 98 discrepancies were noted, which proves a significant decrease since 2019 when the number of discrepancies was 70%. Totally 79% of the discrepancies were estimated to have occurred during the patient's hospital stay. The highest number of discrepancies were found in the medical department and the difference between all inpatient care departments was significant (p <0.0001). Conclusion: The results indicate a decrease in discrepancies since 2019. Further research is necessary to cla

Solid lipid-based formulations (sLBFs) have the potential to increase the oral bioavailability of drugs with poor solubility in water, while counteracting some of the disadvantages of liquid LBFs. The most common experimental set-up to study the performance of LBFs in vitro is the lipolysis assay, during which the LBFs are digested by lipases in an environment mimicking the human small intestine. However, this assay has failed in many cases to correctly predict the performance of LBFs in vivo, highlighting the need for new and improved in vitro assays to evaluate LBFs at the preclinical stage. In this study, the suitability of three different in vitro digestion assays for the evaluation of sLBFs was assessed; the classic one-step intestinal digestion assay, a two-step gastrointestinal digestion assay and a bicompartmental assay permitting the simultaneous monitoring of digestion and permeation of the active pharmaceutical ingredient (API) across an artificial membrane (Lecithin in Dodecane - LiDo). Three sLBFs (M1-M3) with varied composition and ritonavir as model drug were prepared and examined. When comparing the ability of these formulations to keep the drug solubilized in the aqueous phase, all three assays show that M1 performs better, while M3 presents poor performance. However, the classic in vitro intestinal digestion assay fails to provide a clear ranking of the three formulations, something that is more evident when using the two modified and more physiologically relevant assays. Also, the two modified assays provide additional information about the performance of the formulations including the performance in the gastric environment and intestinal flux of the drug. These modified in vitro digestion assays are valuable tools for the development and evaluation of sLBFs to make better informed decisions of which formulations to pursue for in vivo studies.

Gliclazide was approved as a treatment for type 2 diabetes in an era before model-based drug development, and consequently, the recommended doses were not optimised with modern methods. To investigate various dosing regimens of gliclazide, we used publicly available data to characterise the dose-response relationship using pharmacometric models. A literature search identified 21 published gliclazide pharmacokinetic (PK) studies with full profiles. These were digitised, and a PK model was developed for immediate- (IR) and modified-release (MR) formulations. Data from a gliclazide dose-ranging study of postprandial glucose were used to characterise the concentration-response relationship using the integrated glucose-insulin model. Simulations from the full model showed that the maximum effect was 44% of the patients achieving HbA1c <7%, with 11% experiencing glucose <3 mmol/L and the most sensitive patients (i.e., 5% most extreme) experiencing 35 min of hypoglycaemia. Simulations revealed that the recommended IR dose (320 mg) was appropriate with no efficacy gain with increased dose. However, the recommended dose for the MR formulation may be increased to 270 mg, with more patients achieving HbA1c goals (i.e., HbA1c <7%) without a hypoglycaemic risk higher than the resulting risk from the recommended IR dose.

Background and Objective As a result of changes in physiology during pregnancy, the pharmacokinetics (PK) of drugs can be altered. It is unclear whether under- or overexposure occurs in pregnant cancer patients and thus also whether adjustments in dosing regimens are required. Given the severity of the malignant disease and the potentially high impact on both the mother and child, there is a high unmet medical need for adequate and tolerable treatment of this patient population. We aimed to develop and evaluate a semi-physiological enriched model that incorporates physiological changes during pregnancy into available population PK models developed from non-pregnant patient data. Methods Gestational changes in plasma protein levels, renal function, hepatic function, plasma volume, extracellular water and total body water were implemented in existing empirical PK models for docetaxel, paclitaxel, epirubicin and doxorubicin. These models were used to predict PK profiles for pregnant patients, which were compared with observed data obtained from pregnant patients. Results The observed PK profiles were well described by the model. For docetaxel, paclitaxel and doxorubicin, an overprediction of the lower concentrations was observed, most likely as a result of a lack of data on the gestational changes in metabolizing enzymes. For paclitaxel, epirubicin and doxorubicin, the semi-physiological enriched model performed better in predicting PK in pregnant patients compared with a model that was not adjusted for pregnancy-induced changes. Conclusion By incorporating gestational changes into existing population pharmacokinetic models, it is possible to adequately predict plasma concentrations of drugs in pregnant patients which may inform dose adjustments in this population.

Background: Oxycodone active uptake across the blood-brain barrier (BBB) is associated with the putative proton-coupled organic cation (H+/OC) antiporter system. Yet, the activity of this system at the blood-cerebrospinal fluid barrier (BCSFB) is not fully understood. Additionally, sex differences in systemic pharmacokinetics and pharmacodynamics of oxycodone has been reported, but whether the previous observations involve sex differences in the function of the H+/OC antiporter system remain unknown. The objective of this study was, therefore, to investigate the extent of oxycodone transport across the BBB and the BCSFB in female and male Sprague-Dawley rats using microdialysis. Methods: Microdialysis probes were implanted in the blood and two of the following brain locations: striatum and lateral ventricle or cisterna magna. Oxycodone was administered as an intravenous infusion, and dialysate, blood and brain were collected. Unbound partition coefficients (K-p,K-uu) were calculated to understand the extent of oxycodone transport across the blood-brain barriers. Non-compartmental analysis was conducted using Phoenix 64 WinNonlin. GraphPad Prism version 9.0.0 was used to perform t-tests, one-way and two-way analysis of variance followed by Tukey's or Sidak's multiple comparison tests. Differences were considered significant at p < 0.05. Results: The extent of transport at the BBB measured in striatum was 4.44 +/- 1.02 (K-p,K-uu,K-STR), in the lateral ventricle 3.41 +/- 0.74 (K-p,K-uu,K-LV) and in cisterna magna 2.68 +/- 1.01 (K-p,K-uu,K-CM). These K-p,K-uu values indicate that the extent of oxycodone transport is significantly lower at the BCSFB compared with that at the BBB, but still confirm the presence of active uptake at both blood-brain interfaces. No significant sex differences were observed in neither the extent of oxycodone delivery to the brain, nor in the systemic pharmacokinetics of oxycodone. Conclusions: The findings clearly show that active uptake i

The interest for developing antibody-driven therapeutic interventions has exponentially grown over the last few decades. Even though there have been promising leaps in the development of efficacious antibody therapies, problems revolving around production and site-directed delivery of these large macromolecules persist. This is especially pertinent when it comes to designing and producing antibodies to penetrate the blood-brain barrier (BBB) to tackle neurodegenerative diseases. One of the most effective approaches to alleviating this problem is to employ a "Trojan Horse " approach, using receptor-mediated transcytosis, such as those governed by the transferrin receptor (TfR)-mediated pathways, to deliver large protein payloads into the brain. Even though this method is effective, ideal limiting factors, related to how the antibody binds to the TfR, need to be elucidated to improve BBB penetrance. With this said, we have designed and produced a single-chain Fc antibody, conjugated to an scFv8D3 TfR binding motif, creating a single-chain monovalent BBB transporter (scFc-scFv8D3). This recombinant protein is easy to produce and purify, demonstrates monovalent binding to the TfR and is structurally stable at physiologically relevant temperatures. Using an in vitro BBB model system, we show a positive correlation between the concentration of administered antibody and transcytosis efficacy, with scFc-scFv8D3 demonstrating significantly higher transcytosis levels compared with scFv8D3-conjugated bivalent antibodies at elevated administered concentrations. Furthermore, in vivo studies recapitulate the in vitro results, with the scFc-scFv8D3 demonstrating an elevated brain uptake at higher therapeutic doses in wild-type mice, comparable with that of the scFv8D3-conjugated bivalent antibody control. In addition, the half-life of the single-chain monovalent BBB transporter is comparable with that of standard IgG antibodies, indicating that the scFc format does not exacerbate, De två första författarna delar förstaförfattarskapet

Model-based meta-analysis (MBMA) is an approach that integrates relevant summary level data from heterogeneously designed randomized controlled trials (RCTs). This study not only evaluated the predictability of a published MBMA for forced expiratory volume in one second (FEV1) and its link to annual exacerbation rate in patients with chronic obstructive pulmonary disease (COPD) but also included data from new RCTs. A comparative effectiveness analysis across all drugs was also performed. Aggregated level data were collected from RCTs published between July 2013 and November 2020 (n = 132 references comprising 156 studies) and combined with data used in the legacy MBMA (published RCTs up to July 2013 - n = 142). The augmented data (n = 298) were used to evaluate the predictive performance of the published MBMA using goodness-of-fit plots for assessment. Furthermore, the model was extended including drugs that were not available before July 2013, estimating a new set of parameters. The legacy MBMA model predicted the post-2013 FEV1 data well, and new estimated parameters were similar to those of drugs in the same class. However, the exacerbation model overpredicted the post-2013 mean annual exacerbation rate data. Inclusion of year when the study started on the pre-treatment placebo rate improved the model predictive performance perhaps explaining potential improvements in the disease management over time. The addition of new data to the legacy COPD MBMA enabled a more robust model with increased predictability performance for both endpoints FEV1 and mean annual exacerbation rate.

Small synthetic mimics of cationic antimicrobial peptides represent a promising class of compounds with leads in clinical development for the treatment of persistent microbial infections. The activity and selectivity of these compounds rely on a balance between hydrophobic and cationic components, and here, we explore the activity of 19 linear cationic tripeptides against five different pathogenic bacteria and fungi, including clinical isolates. The compounds incorporated modified hydrophobic amino acids inspired by motifs often found in bioactive marine secondary metabolites in combination with different cationic residues to probe the possibility of generating active compounds with improved safety profiles. Several of the compounds displayed high activity (low mu M concentrations), comparable with the positive controls AMC-109, amoxicillin, and amphotericin B. A higher activity was observed against the fungal strains, and a low in vitro off-target toxicity was observed against erythrocytes and HeLa cells, thereby illustrating effective means for tuning the activity and selectivity of short antimicrobial peptides.

The main focus of this thesis has been on Quantitative Structure Activity Relationship (QSAR) modeling using methods producing valid measures of uncertainty. The goal of QSAR is to prospectively predict the outcome from assays, such as ADMET (Absorption, Distribution, Metabolism, Excretion), toxicity and on- and off-target interactions, for novel compounds. QSAR modeling offers an appealing alternative to laboratory work, which is both costly and time-consuming, and can be applied earlier in the development process as candidate drugs can be tested in silico without requiring to synthesize them first. A common theme across the presented papers is the application of conformal and probabilistic prediction models, which are used in order to associate predictions with a level of their reliability – a desirable property that is essential in the stage of decision making. In Paper I we studied approaches on how to utilize biological assay data from legacy systems, in order to improve predictive models. This is otherwise problematic since mixing data from separate systems will cause issues for most machine learning algorithms. We demonstrated that old data could be used to augment the proper training set of a conformal predictor to yield more efficient predictions while preserving model calibration. In Paper II we studied a new approach of predicting metabolic transformations of small molecules based on transformations encoded in SMIRKS format. In this work use used the probabilistic Cross-Venn-ABERS predictor which overall worked well, but had difficulty in modeling the minority class of imbalanced datasets. In Paper III we studied metabolomics data from patients diagnosed with Multiple Sclerosis and found a set of 15 discriminatory metabolites that could be used to classify patients from a validation cohort into one of two sub types of the disease with high accuracy. We further demonstrated that conformal prediction could be useful for tracking the progression of the disea

Background Suboptimal exposure to antituberculosis (anti-TB) drugs has been associated with unfavourable treatment outcomes. We aimed to investigate estimates and determinants of first-line anti-TB drug pharmacokinetics in children and adolescents at a global level. Methods We systematically searched MEDLINE, Embase and Web of Science (1990–2021) for pharmacokinetic studies of first-line anti-TB drugs in children and adolescents. Individual patient data were obtained from authors of eligible studies. Summary estimates of total/extrapolated area under the plasma concentration–time curve from 0 to 24 h post-dose (AUC0–24) and peak plasma concentration (Cmax) were assessed with random-effects models, normalised with current World Health Organization-recommended paediatric doses. Determinants of AUC0–24 and Cmax were assessed with linear mixed-effects models. Results Of 55 eligible studies, individual patient data were available for 39 (71%), including 1628 participants from 12 countries. Geometric means of steady-state AUC0–24 were summarised for isoniazid (18.7 (95% CI 15.5–22.6) h·mg·L−1), rifampicin (34.4 (95% CI 29.4–40.3) h·mg·L−1), pyrazinamide (375.0 (95% CI 339.9–413.7) h·mg·L−1) and ethambutol (8.0 (95% CI 6.4–10.0) h·mg·L−1). Our multivariate models indicated that younger age (especially <2 years) and HIV-positive status were associated with lower AUC0–24 for all first-line anti-TB drugs, while severe malnutrition was associated with lower AUC0–24 for isoniazid and pyrazinamide. N-acetyltransferase 2 rapid acetylators had lower isoniazid AUC0–24 and slow acetylators had higher isoniazid AUC0–24 than intermediate acetylators. Determinants of Cmax were generally similar to those for AUC0–24. Conclusions This study provides the most comprehensive estimates of plasma exposures to first-line anti-TB drugs in children and adolescents. Key determinants of drug exposures were identified. These may be relevant for population-specific dose adjustment or individualis

Fused deposition modeling (FDM) and selective laser sintering (SLS) are two of the most employed additive manufacturing (AM) techniques within the pharmaceutical research field. Despite the numerous advantages of different AM methods, their respective drawbacks have yet to be fully addressed, and therefore combinatorial systems are starting to emerge. In the present study, hybrid systems comprising SLS inserts and a two-compartment FDM shell are developed to achieve controlled release of the model drug theophylline. Via the use of SLS a partial amorphization of the drug is demonstrated, which can be advantageous in the case of poorly soluble drugs, and it is shown that sintering parameters can regulate the dosage and release kinetics of the drug from the inserts. Furthermore, via different combinations of inserts within the FDM-printed shell, various drug release patterns, such as a two-step or prolonged release, can be achieved. The study serves as a proof of concept, highlighting the advantages of combining two AM techniques, both to overcome their respective shortcomings and to develop modular and highly tunable drug delivery devices.

Large batches of placebo and drug-loaded solid dosage forms were successfully fabricated using selective laser sintering (SLS) 3D printing in this study. The tablet batches were prepared using either copovidone (N-vinyl-2-pyrrolidone and vinyl acetate, PVP/VA) or polyvinyl alcohol (PVA) and activated carbon (AC) as radiation absorbent, which was added to improve the sintering of the polymer. The physical properties of the dosage forms were evaluated at different pigment concentrations (i.e., 0.5 and 1.0 wt%) and at different laser energy inputs. The mass, hardness, and friability of the tablets were found to be tunable and structures with greater mass and mechanical strength were obtained with increasing carbon concentration and energy input. Amorphization of the active pharmaceutical ingredient in the drug-loaded batches, containing 10 wt% naproxen and 1 wt% AC, was achieved in-situ during printing. Thus, amorphous solid dispersions were prepared in a single-step process and produced tablets with mass losses below 1 wt%. These findings show how the properties of dosage forms can be tuned by careful selection of the process parameters and the powder formulation. SLS 3D printing can therefore be considered to be an interesting and promising technique for the fabrication of personalized medicines.

Pharmaceutical formulation of oral dosage forms is continuously challenged by the low solubility of new drug candidates. Pickering emulsions, emulsions stabilized with solid particles, are a promising alternative to surfactants for developing long-term stable emulsions that can be tailored for controlled release of lipophilic drugs. In this work, a non-emulsifying lipid-based formulation (LBF) loaded with fenofibrate was formulated into an oilin-water (O/W) emulsion synergistically stabilized by stearic acid and silica (SiO2) nanoparticles. The emulsion had a droplet size of 341 nm with SiO2 particles partially covering the oil-water interface. In vitro lipid digestion was faster for the emulsion compared to the corresponding LBF due to the larger total surface area available for digestion. Cellulose biopolymers were added to the emulsion to produce a gel for semi-solid extrusion (SSE) 3D printing into tablets. The emulsion gel showed suitable rheological attributes for SSE, with a trend of higher viscosity, yield stress, and storage modulus (G & PRIME;), compared to a conventional self-emulsifying lipid-based emulsion gel. The developed emulsion gel allows for a non-emulsifying LBF to be transformed into solid dosage forms for rapid lipid digestion and drug release of a poorly water-soluble drug in the small intestine.

Background:Recent studies have reported ethnic differences in vincristine exposure and outcomes such as toxicity. This resulted in the hypothesis of subtherapeutic dosing in African children. To optimize individual treatment, a strategy to identify subtherapeutic exposure using therapeutic drug monitoring is essential. The aim of the current study was to develop a strategy for therapeutic drug monitoring of vincristine in African children to meet the following criteria: (1) identify patients with low vincristine exposure with sufficient sensitivity (>70%), (2) determine vincristine exposure with a limited sampling strategy design of 3 samples, and (3) allow all samples to be collected within 4 hours after administration. Methods:An in silico simulation study was performed using a previously described population pharmacokinetic model and real-life demographic dataset of Kenyan and Malawian pediatric oncology patients. Two different therapeutic drug monitoring strategies were evaluated: (1) Bayesian approach and (2) pharmacometric nomogram. The sampling design was optimized using the constraints described above. Sensitivity analysis was performed to investigate the influence of missing samples, erroneous sampling times, and different boundaries on the nomogram weight bands. Results:With the Bayesian approach, 43.3% of the estimated individual exposure values had a prediction error of & GE;20% owing to extremely high shrinkage. The Bayesian approach did not improve with alternative sampling designs within sampling constraints. However, the pharmacometric nomogram could identify patients with low vincristine exposure with a sensitivity, specificity, and accuracy of 75.1%, 76.4%, and 75.9%, respectively. The pharmacometric nomogram performed similarly for different weight bands. Conclusions:The pharmacometric nomogram was able to identify patients with low vincristine exposure with high sensitivity, with 3 blood samples collected at 1, 1.5, and 4 hours after admin

Fluorescence staining techniques, such as Cell Painting, together with fluorescence microscopy have proven invaluable for visualizing and quantifying the effects that drugs and other perturbations have on cultured cells. However, fluorescence microscopy is expensive, time-consuming, labor-intensive, and the stains applied can be cytotoxic, interfering with the activity under study. The simplest form of microscopy, brightfield microscopy, lacks these downsides, but the images produced have low contrast and the cellular compartments are difficult to discern. Nevertheless, by harnessing deep learning, these brightfield images may still be sufficient for various predictive purposes. In this study, we compared the predictive performance of models trained on fluorescence images to those trained on brightfield images for predicting the mechanism of action (MoA) of different drugs. We also extracted CellProfiler features from the fluorescence images and used them to benchmark the performance. Overall, we found comparable and largely correlated predictive performance for the two imaging modalities. This is promising for future studies of MoAs in time-lapse experiments for which using fluorescence images is problematic. Explorations based on explainable AI techniques also provided valuable insights regarding compounds that were better predicted by one modality over the other., De två första författarna delar förstaförfattarskapetDe två sista författarna delar sistaförfattarskapet

Development of subtype-selective leads is essential in drug discovery campaigns targeting G protein-coupled receptors (GPCRs). Herein, a structure-based virtual screening approach to rationally design subtype-selective ligands was applied to the A1 and A2A adenosine receptors (A1R and A2AR). Crystal structures of these closely related subtypes revealed a non-conserved subpocket in the binding sites that could be exploited to identify A1R selective ligands. A library of 4.6 million compounds was screened computationally against both receptors using molecular docking and 20 A1R selective ligands were predicted. Of these, seven antagonized the A1R with micromolar activities and several compounds displayed slight selectivity for this subtype. Twenty-seven analogs of two discovered scaffolds were designed, resulting in antagonists with nanomolar potency and up to 76-fold A1R-selectivity. Our results show the potential of structure-based virtual screening to guide discovery and optimization of subtype-selective ligands, which could facilitate the development of safer drugs.