The word communication originates from the Latin word communicare that means to do something in common. When human beings communicate with each other, we share thoughts, emotions, values and actions. The foundation in communication is found within the interpersonal communication, which is the act of communication between two persons. All types of communications include of verbal and nonverbal acts of communication. The verbal communication consists of words either in speech or writing, the nonverbal act implies gestures, frequency of the tone and facial expressions. Within the pharmaceutical profession, good communication between the pharmacist and the customer is important and can affect the customer’s health and quality of life in both direct as well as indirect ways. In recent years, the pharmacist's role in the pharmacy has drastically changed. Nowadays the care of the customer has gained more significance than before. To improve customer health and quality of life it is important that the pharmacist acts to promote a good relationship with the customer and the foundation for this relationship should be built on good terms of communication. The purpose of this study was to study how common it is with communication errors between pharmacist and customer, and to demonstrate probable underlying causes. Secondary questions were, how is the drug advice the pharmacist provides affected by communication errors? Collection of data for the study was done with structured observation charts, where the customer and pharmacist were strictly observed. A total of 316 meetings were observed and the data collected referred to prescriptions. In more than one-third of the observed meetings, there were communication errors between the pharmacist and the customer. Communication errors that arose concerned lack of eye contact, language barriers, choice of questions, background noise from colleagues and customers and discussions from generic exchanges. To reduce future communication errors, the pharmacist's actions should be strengthened, such as eye contact, clear follow-up questions and improved feedback.

<p>In drug development clinical trials are designed to investigate whether a new treatment is safe and has the desired effect on the disease in the target patient population. Categorical endpoints, for example different ranking scales or grading of adverse events, are commonly used to measure effects in the trials. </p><p>Pharmacokinetic/Pharmacodynamic (PK/PD) models are used to describe the plasma concentration of a drug over time and its relationship to the effect studied. The models are utilized both in drug development and in discussions with drug regulating authorities. Methods for incorporation of ordered categorical data in PK/PD models were studied using a non-linear mixed effects modelling approach as implemented in the software NONMEM. The traditionally used proportional odds model was used for analysis of a 6-grade sedation scale in acute stroke patients and for analysis of a T-cell receptor expression in patients with Multiple Sclerosis, where the results also were compared with an analysis of the data on a continuous scale. Modifications of the proportional odds model were developed to enable analysis of a spontaneously reported side-effect and to analyze situations where the scale used is heterogeneous or where the drug affects the different scores in the scale in a non-proportional way. The new models were compared with the proportional odds model and were shown to give better predictive performances in the analyzed situations. </p><p>The results in this thesis show that categorical data obtained in clinical trials with different design and different categorical endpoints successfully can be incorporated in PK/PD models. The models developed can also be applied to analyses of other ordered categorical scales than those presented.</p>

Nasal administration has potential for the treatment of indications requiring a fast onset of effect or for drugs with low oral bioavailability. Liquid nasal sprays are relatively common, but can be associated with suboptimal absorption from the nasal cavity; this thesis shows that nasal absorption can be significantly enhanced with a dry powder formulation. It was shown that interactive mixtures, consisting of fine drug particles adhered to the surface of mucoadhesive carrier particles, could be created in a particle size suitable for nasal administration. Sodium starch glycolate (SSG), a common tablet excipient, was used as carrier material. In vitro evaluation of the formulation indicated that the mucoadhesion of the carrier was unlikely to be affected by the addition of a drug. The powder formulation did not improve the in vitro transfer of dihydroergotamine across porcine nasal mucosa compared with a liquid formulation; however, the results were associated with methodological shortcomings. The binding of model substances to SSG and three other excipients was evaluated. Ion exchange interactions were for example detected between SSG and cationic drugs, but these interactions were most extensive at low salt concentrations and should unlikely affect in vivo bioavailability at physiological salt concentrations. Absorption of the peptide drug desmopressin from the SSG nasal formulation, from a novel sublingual tablet formulation and from a commercial nasal liquid spray was evaluated in a clinical trial. While no improvement over the liquid spray was seen with the sublingual tablet, plasma concentrations after the nasal powder formulation were three times higher than those after the liquid spray. All formulations were well accepted by the volunteers. The use of currently available mucoadhesive carrier particles in interactive mixtures offers potential for a new method of producing nasal powder formulations that should also be applicable to large scale production.

Due to increasing problems with bacterial resistance development, there is a growing need for identifying new types of antibiotics. Antimicrobial peptides constitute an interesting group of substances for this purpose, since they are believed to act mainly by disrupting the bacterial membrane, which is a fast and non-specific mechanism. In order to understand the details on this action simplified phospholipid model membranes based on liposomes, monolayers and bilayers, were employed in this thesis. By in situ ellipsometry studies on supported lipid bilayers in combination with leakage from liposomes it was found that peptide-induced membrane rupture to a great extent is related to peptide adsorption. The peptide activity and mechanism of action is highly dependent on peptide properties such as length, topology, charge, and hydrophobicity. Electrostatic interactions are crucial for peptide adsorption, whereas α-helix formation is of less importance, demonstrated by the dominating peptide conformation being random coil both in absence and presence of membranes, as investigated by circular dichroism. Comparable effects were observed in both mono- and bilayer systems, showing that formation of transmembrane structures is no prerequisite for membrane rupture by complement-derived peptides. Electrochemical studies on these peptides further demonstrated that hydrophobic interactions facilitate peptide penetration into the membrane, causing defects in close proximity to the peptides, while strong electrostatic interactions arrest the peptide in the headgroup region. Increasing the peptide hydrophobicity, by e.g., tryptophan end-tagging, also increases salt resistance. Good correlations were found between model membrane investigations and antibacterial activity towards both Gram-negative and Gram-positive bacteria, showing that membrane rupture is a key mechanism of action for the peptides investigated. In addition, for all peptides investigated cell toxicity is low.

Lightly cross-linked polyelectrolyte microgels are materials with interesting properties for a range of applications. For instance, the volume of these particles can be drastically changed in response to pH, ionic strength, temperature, or the concentration of specific ions and metabolites. In addition, microgel particles can bind substantial amounts of oppositely charged substances, such as proteins and peptides, and release them upon changes in the external environment. Consequently, microgels have potential in catalysis, photonics, biomaterials, and not at least, as protective and stimuli-sensitive carriers for protein and peptide drugs. In this thesis, the interaction between anionic microgels and cationic peptides was investigated by monitoring microgel deswelling and reswelling in response to peptide binding and release using micromanipulator-assisted light microscopy. In addition, peptide distribution in microgels was analyzed with confocal laser scanning microscopy and peptide uptake determined with solution depletion measurements. The aim of the thesis was to clarify how parameters such as peptide size, charge density, pH, ionic strength and hydrophobicity influences the peptide binding to, distribution in and release from, polyelectrolyte microgels. Results obtained in this thesis show that electrostatic attraction is a prerequisite for interaction to occur although non-electrostatic contributions are responsible the finer details of the interactions. The size and charge density of the interacting peptides play a major role, as large and highly charged peptides are restricted to enter and interact with the microgel core, thus displaying a surface-confined distribution. The peptide-microgel interaction strength is highly reflected in the probability of peptides to be detached from the gel network. For instance, reducing the electrostatic interactions by adding salt induces significant peptide release of sufficiently small and moderately charged peptides, whereas longer and more highly charged peptides is retained in the microgel network due to the strong interaction, insufficient salt screening, and gel network pore size restriction. Decreasing the charge density of microgel network and/or peptides increases the probability for peptide detachment tremendously. To summarize, interactions occurring in oppositely charged microgel-peptide systems can be tuned by varying parameters such as charge density and peptide size and through this, the peptide uptake, distribution and release can be controlled to alter the performance of microgels in peptide drug delivery.

The blood-brain barrier is formed by tightly joined capillary cells with transporter proteins and acts as to regulate the brain concentration of nutrients as well as many drugs. When developing central nervous system drugs it is necessary to measure the unbound drug concentration in the brain, i.e. the unbound brain exposure. This is to ensure that the drug reaches the site of action. Furthermore, when designing new drugs it is extremely valuable to be able to predict brain exposure from a tentative drug structure. Established methods to measure total drug concentrations are of limited (if any) utility since the pharmacologically active, unbound, concentration is not obtained. The aim of the conducted research was to develop an efficient methodology to measure unbound drug in the brain and to generate a dataset for developing computational prediction models describing the relationship between drug structure and unbound brain exposure. First it was demonstrated that unbound brain exposure can be efficiently assessed using a combination of total drug concentrations in the brain and separate measurements of drug binding in the brain slices. The in vitro brain slice method was refined and made high-throughput. Improvements were also made to the in vivo measurements of total concentrations by introducing an appropriate correction for drug in residual blood. Modeling of a 43-drug dataset in the rat showed that unbound brain exposure is related to the drug hydrogen bonding potential and not to lipid solubility, which contrasts the common understanding. Further, the drug concentrations in cerebrospinal fluid approximated unbound concentrations in the brain (r2=0.80) and were also correlated with corresponding measurements in humans (r2=0.56). Therefore, rat-derived prediction models can be used when designing drugs for humans. This thesis work has provided drug industry and academia with efficient tools to obtain and to use relevant estimates of drug exposure in the brain for evaluating drugs candidates.

In drug development clinical trials are designed to investigate whether a new treatment is safe and has the desired effect on the disease in the target patient population. Categorical endpoints, for example different ranking scales or grading of adverse events, are commonly used to measure effects in the trials. Pharmacokinetic/Pharmacodynamic (PK/PD) models are used to describe the plasma concentration of a drug over time and its relationship to the effect studied. The models are utilized both in drug development and in discussions with drug regulating authorities. Methods for incorporation of ordered categorical data in PK/PD models were studied using a non-linear mixed effects modelling approach as implemented in the software NONMEM. The traditionally used proportional odds model was used for analysis of a 6-grade sedation scale in acute stroke patients and for analysis of a T-cell receptor expression in patients with Multiple Sclerosis, where the results also were compared with an analysis of the data on a continuous scale. Modifications of the proportional odds model were developed to enable analysis of a spontaneously reported side-effect and to analyze situations where the scale used is heterogeneous or where the drug affects the different scores in the scale in a non-proportional way. The new models were compared with the proportional odds model and were shown to give better predictive performances in the analyzed situations. The results in this thesis show that categorical data obtained in clinical trials with different design and different categorical endpoints successfully can be incorporated in PK/PD models. The models developed can also be applied to analyses of other ordered categorical scales than those presented.

Background: Familial hypercholesterolemia (FH) is a genetic disorder estimated to affect 0,4 % of the world's population (1 in 250). Patients with FH have abnormally high LDL-cholesterol.  Aim: The aim of this study was to estimate the prevalence of FH in Stockholm County and to evaluate the health economic impact of diagnosing people with FH early in life. Methods: Two algorithms were used to estimate the number of people with high LDLcholesterol. The first method applied data on cholesterol measurements from patients in Stockholm County between 2006-2008 and a modified version of Dutch Lipid Clinic Network. The second method was based on dispensed prescriptions of ezetimibe, lomitapide, evolucumab and alirocumab during 2019. A health economic model was created to estimate the economical outcome of diagnosing and treating patients early before undergoing a cardiovascular event. Results: The prevalence of FH in Stockholm County was estimated to 0.63 %, corresponding to a total of 12 000 individuals. The accumulated costs over 20 years for FH is estimated to be more than 1,1 billion SEK for diagnosed and treated patients, and 1,7 billion SEK for undiagnosed and untreated patients. Conclusions: The prevalence of FH in Stockholm County is probably higher than previously suggested. Early diagnosis and treatment is an investment for society and necessary for the patients to prevent cardiovascular events and improve quality of life.

Background: High blood pressure (BP) or hypertension is defined as a systolic and diastolic pressure over 140/90 mmHg. High blood pressure increases the risk for premature death, and previous research has shown that many patients do not reach targets and that there are differences between primary healthcare centers in the proportion of patient reaching targets. The reasons for these variations, however, are unknown. Aim: To investigate variations in blood pressure target achievement between primary care centers in Stockholm county and how different factors such as practice size, ownership, socioeconomic and antihypertensive drug treatment can influence this diversity. Method(s): This study was designed as a cross-sectional register study with a descriptive quantitative perspective. Data was collected from three sources: National Primary Care Quality register, Care Need Index for healthcare in Stockholm region and Stockholm County Council data warehouse VAL. The study included 179 out of all 227 primary care centers in the region. The proportion of all patients with hypertension reaching targets was assessed each year during 2019-2021, and correlations studied for potential predictors. Results: there was a variation between primary care centers in target blood pressure fulfillment, ranging from 22-66% during 2021, 23-63% during 2020 and 33-66% during 2019, respectively. There was no overall difference between public and private centers in the proportion of patients reaching targets, but a larger practice variation among private centers. No correlation was found between the other studied factors and target blood pressure fulfillment during 2021. Conclusion: There was a variation between primary care centers in the proportion of patients reaching blood pressure targets. Different practices may change ranking between years and other factors than practice size, ownership and socioeconomic appears to explain the variation.

Introduction Human immunodeficiency virus (HIV) is a double stranded RNA retrovirus. According to the World Health Organization more than 30 million individuals were estimated to have HIV by the end of 2020, about 60% of which are in the African region. Pre-treatment drug resistance (PDR) can be defined as the resistant virus strains transmitted at the time of infection or acquired during previous exposure to ARV. This study asses the effect of drivers in PDR. Method: This study was conducted with data extracted from published, publicly available data bases and reports by international organizations. The main sources were United Nation data bases and published reports from World Health Organization.  Inferential statistics were used to assess the PDR to anti-retroviral drugs. A linear regression model was used to investigate the association between PDR and previous exposure to anti-retrovirals and anti-retroviral therapy, pre-exposure prophylaxis, national health expenditure, human development index, and drug stock-out for different classes of anti-retroviral drugs.   Results: The result indicated that NNRTI drug resistance was most common, and seven out of 29 countries had PDR to all four drug classes. The human development index was positively associated with INSTI and PI PDR (p&lt;0.05), while NNRTI and NRTI were mainly positively associated with previous exposure to anti-retrovirals. Conclusion: This study assessed the impact of socio-economics determinants (human development index and national health expenditure), drug logistic determinants (stock-out), and patients’ determinants (adherence and previous exposure to any kind of anti-retrovirals) on PDR. For expensive drug classes (PI and INSTI) the resistance was positively associated with human development index. Previous exposure to anti-retrovirals was associated with increased resistance in NNRTI and NRTI.