Quantitative systems pharmacology model of erythropoiesis to simulate therapies targeting anemia due to chronic kidney disease

Anemia induced by chronic kidney disease (CKD) has multiple underlying mechanistic causes and generally worsens as CKD progresses. Erythropoietin (EPO) is a key endogenous protein which increases the number of erythrocyte progenitors that mature into red blood cells that carry hemoglobin (Hb). Recombinant human erythropoietin (rHuEPO) in its native and re-engineered forms is used as a therapeutic to alleviate CKD-induced anemia by stimulating erythropoiesis. However, due to safety risks associated with erythropoiesis-stimulating agents (ESAs), a new class of drugs, prolyl hydroxylase inhibitors (PHIs), has been developed. Instead of administering exogenous EPO, PHIs facilitate the accumulation of HIF-α, which results in the increased production of endogenous EPO. Clinical trials for ESAs and PHIs generally involve balancing decisions related to safety and efficacy by carefully evaluating the criteria for patient selection and adaptive trial design. To enable such decisions, we developed a quantitative systems pharmacology (QSP) model of erythropoiesis which captures key aspects of physiology and its disruption in CKD. Furthermore, CKD virtual populations of varying severities were developed, calibrated, and validated against public data. Such a model can be used to simulate alternative trial protocols while designing phase 3 clinical trials, as well as an asset for reverse translation in understanding emerging clinical data

Anemia management in end stage renal disease patients undergoing dialysis: a comprehensive approach through machine learning techniques and mathematical modeling

Kidney impairment has global consequences in the organism homeostasis and a disorder like Chronic Kidney Disease (CKD) might eventually exacerbates into End Stage Renal Disease (ESRD) where a complete renal replacement therapy like dialysis is necessary. Dialysis partially reintegrates the blood ltration process; however, even when it is associated to a pharmacological therapy, this is not su fficient to completely replace the renal endocrine role and causes the development of common complications, like CKD secondary anemia (CKD-anemia) The availability of exogenous Erythropoiesis Stimulating Agents (ESA, synthetic molecules with similar structure and same mechanism of action as human erythropoietin) improved the treatment of CKD-anemia although the clinical outcomes are still not completely successful. In particular, for ERSD dialysis patients main di culties in the selection of an optimal therapy dosing derive from the high intra- and inter-individual response variability and the temporal discrepancy between the short ESA permanence in the blood (hours) and the long Red Blood Cells lifespan (months). The aim of this thesis has been to describe the development of the Anemia Control Model (ACM), a tool designed to support physicians in managing anemia for ESRD patines undergoing dialysis. Five main pillars constitute the foundation of this work: - Understanding the medical problem; - Availability of the data needed to derive the models; - Mathematical and Machine Learning modeling; - Development of a product usable at the point of care; - Medical device certi cation and clinical evaluation of the developed product. The understanding of the medical problem is fundamental for two reasons: firstly because the medical problem must be the driver of the product scope and consequently of its design; secondly because a good understanding of the medical problem is of fundamental importance to develop optimized models. In the case of anemia management the drug dosing is an important task where predictive models could support physicians to improve the treatment quality. In particular, considering that hemoglobin is the typical parameter used to measure anemia, our model were tailored to predict hemoglobin response to the two main drugs normally used to correct anemia, that is ESA and Iron. In a mathematical model based on di erential equations, like the one presented in this thesis, the knowledge of the main physiological processes related to anemia is the base to properly design the equations. A machine learning approach in principle can be built with no hypotesis, because it relays in learning from data, nevertheless knowledge of the domain helps to make better use of the available data. The medical problem has been discussed in Chapter 1. The availability of a huge database of very well structured data was basic for the development of models. Quality of the data is another important aspect. Chapter 2 gives the reader an overview of the available data.. The core of the ACM is the capability to predict for each patient the future hemoglobin concentrations as a function of past patient's clinical history and future drug prescription. By means of well performing and personalized predictive model it is possible to simulate how, for each specific c patient, di erent doses would a ffect hemoglobin trends. Mathematical and machine learning models present both advantages and limitations. Chapter 3 describes the mathematical model and analyzes its performances, while Chapter 4 is dedicated to the machine learning models. In our case the machine learning approach resulted more suitable for our scope, because its was well performing on the entire population, more stable and, once trained, very quick in elaborating the prediction. Once the predictive model was obtained, the next step was to wrap it into a service that could be consumed by a third party system (for example an app or a clinical system) where physicians could benefi t from the model prediction capability. To achieve that, firstly an algorithm for the dose selection was developed; secondly, a data structure for the communication with the third party system was defi ned; fi nally, the whole package was wrapped in a web service. These arguments have been discussed in the rst part of Chapter 5. Mistakes in ESA or Iron dosing might have serious consequences on patients' health, for this reason ACM intended use was limited to provide dose suggestions only; physicians must evaluate them and decide whether to accept or reject them. Nevertheless, such a tool could be considered as Medical Device under European Medical Device Directive (MDD); for this reason, to be on the safe side, it was decided to certify the ACM as medical device. A novel approach was developed to perform the risk assessment, the main idea being that ACM might generate risks when a dose suggestion is produced based on a wrong prediction. To assess this risk the model error distribution over the test set was utilized as estimation of the error distribution of the live system. Finally, a clinical evaluation of the ACM in three pilot clinics has been performed before deciding to roll-out the tool in more clinics. These arguments have been discussed in the second part of Chapter 5

The European Hematology Association Roadmap for European Hematology Research: a consensus document

The European Hematology Association (EHA) Roadmap for European Hematology Research highlights major achievements in diagnosis and treatment of blood disorders and identifies the greatest unmet clinical and scientific needs in those areas to enable better funded, more focused European hematology research. Initiated by the EHA, around 300 experts contributed to the consensus document, which will help European policy makers, research funders, research organizations, researchers, and patient groups make better informed decisions on hematology research. It also aims to raise public awareness of the burden of blood disorders on European society, which purely in economic terms is estimated at €23 billion per year, a level of cost that is not matched in current European hematology research funding. In recent decades, hematology research has improved our fundamental understanding of the biology of blood disorders, and has improved diagnostics and treatments, sometimes in revolutionary ways. This progress highlights the potential of focused basic research programs such as this EHA Roadmap. The EHA Roadmap identifies nine ‘sections’ in hematology: normal hematopoiesis, malignant lymphoid and myeloid diseases, anemias and related diseases, platelet disorders, blood coagulation and hemostatic disorders, transfusion medicine, infections in hematology, and hematopoietic stem cell transplantation. These sections span 60 smaller groups of diseases or disorders. The EHA Roadmap identifies priorities and needs across the field of hematology, including those to develop targeted therapies based on genomic profiling and chemical biology, to eradicate minimal residual malignant disease, and to develop cellular immunotherapies, combination treatments, gene therapies, hematopoietic stem cell treatments, and treatments that are better tolerated by elderly patients

The European Hematology Association Roadmap for European Hematology Research. A Consensus Document

Abstract The European Hematology Association (EHA) Roadmap for European Hematology Research highlights major achievements in diagnosis and treatment of blood disorders and identifies the greatest unmet clinical and scientific needs in those areas to enable better funded, more focused European hematology research. Initiated by the EHA, around 300 experts contributed to the consensus document, which will help European policy makers, research funders, research organizations, researchers, and patient groups make better informed decisions on hematology research. It also aims to raise public awareness of the burden of blood disorders on European society, which purely in economic terms is estimated at Euro 23 billion per year, a level of cost that is not matched in current European hematology research funding. In recent decades, hematology research has improved our fundamental understanding of the biology of blood disorders, and has improved diagnostics and treatments, sometimes in revolutionary ways. This progress highlights the potential of focused basic research programs such as this EHA Roadmap. The EHA Roadmap identifies nine sections in hematology: normal hematopoiesis, malignant lymphoid and myeloid diseases, anemias and related diseases, platelet disorders, blood coagulation and hemostatic disorders, transfusion medicine, infections in hematology, and hematopoietic stem cell transplantation. These sections span 60 smaller groups of diseases or disorders. The EHA Roadmap identifies priorities and needs across the field of hematology, including those to develop targeted therapies based on genomic profiling and chemical biology, to eradicate minimal residual malignant disease, and to develop cellular immunotherapies, combination treatments, gene therapies, hematopoietic stem cell treatments, and treatments that are better tolerated by elderly patients. Received December 15, 2015. Accepted January 27, 2016. Copyright © 2016, Ferrata Storti Foundatio

Anaemia, Iron-Deficiency and Reducing Transfusion in Cardiac Surgery and A Novel Method for the Measurement of Total Haemoglobin Mass

Anaemia and iron-deficiency are common in cardiac surgical patients and are associated with poor surgical and patient-centred outcomes. Pre-operative anaemia is increasingly being treated with intravenous iron despite a lack of high-quality evidence of its effectiveness. This thesis explores these topics with a literature review exploring anaemia, iron-deficiency, and transfusion in cardiac surgery, and further review on transfusion risk-prediction models, and treatment of pre-operative anaemia with intravenous iron. The first methodological chapter describes the development of a new risk-scoring system to predict those who are likely to require peri-operative red blood cell transfusion in cardiac surgical patients in the UK. This risk scoring system was then modified and recalibrated using an Australian database to create an alternative score applicable to that population, described in the subsequent chapter. The use of intravenous iron has increased significantly since the introduction of new iron-preparations and is now recommended in many treatment pathways and guidelines. This has occurred in advance of high-quality evidence that it can effectively treat anaemia in the pre-operative period and have any meaningful effect on patient outcomes. Chapter 5 describes a UK-wide multicentre trial that demonstrated that IV iron can significantly increase haemoglobin concentration in cardiac surgical patients in the pre-operative period. Challenges in the recruitment for larger studies of anaemic cardiac surgical patients led to an exploration of the recent trends in anaemia-rates over the last 5-7 years, which is described in Chapter 6. This demonstrates that anaemia rates in certain areas have decreased significantly over that period and there has been concomitant exponential increase in the use of intravenous iron preparations in various medical settings. The final methodological chapter describes a novel method for measuring total haemoglobin mass, which may be a more appropriate method of assessing anaemia in various disease states. Previous methods have been difficult to establish and complicated to undertake. This chapter describes a new method using a modification of an existing respiratory function test which is demonstrated to be a simple method of estimating total haemoglobin mass and plasma volume

Clinical and Laboratory Measurement to Improve Patient Blood Management: Foundations to the Three Pillar Framework

Transfusion may be a life-saving procedure. However, history shows that the risks of transfusion have been underestimated and transfusion overused. Blood has been considered dispensable and inadequate thought given to its management, not just to prevent transfusion, but to maximise patient outcomes. Voices heralding the need for blood optimisation and conservation throughout the twentieth century have combined to develop a field known as patient blood management. Patient blood management has been described in terms of three pillars, primarily from a perioperative perspective: optimising the blood pre-operatively; minimising blood loss intraoperatively; and understanding and improving tolerance of anaemia. In this thesis I explore each pillar and argue that improving the way we measure blood-related outcomes has the potential to enhance patient blood management and the approach to transfusion therapy. Iron deficiency is the most common cause for anaemia worldwide. It is particularly common in pregnancy where it can impact the mother's quality of life, the need for transfusion and potentially have far-reaching effects for children. Despite this, there is a lack of consensus on recognising and treating it during pregnancy. I have explored the use of novel red cell and reticulocyte indices, readily available from automated blood count analysers, as tools for detecting iron deficiency. While effective, these were no better than mean cell volume, although as a screening tool, a higher cut-off value is required. I also argue that there is value is screening with ferritin during pregnancy and show that this is best applied in first trimester. Red cell transfusion guidelines advocate transfusion based on individual patient needs rather than specific haemoglobin triggers. Measuring this is difficult and most randomised studies have transfused solely based on haemoglobin. I explored tolerance of anaemia in a different light - near infrared. Near infrared spectroscopy can measure tissue oxygenation and provides a potential transfusion trigger. A systematic literature review showed that tissue oxygenation is affected by anaemia and does respond to changes in haemoglobin. However, there was too much heterogeneity to recommend routine clinical use for transfusion decisions, perhaps as it was most frequently used in acute settings where reduced blood flow is a confounding factor. I therefore explored its utility in chronic anaemia setting and with exercise to see whether poor muscle oxygenation is a limiting factor for activity in anaemia. While there was a measurable impact, there remains too much heterogeneity to identify a transfusion trigger based on tissue oxygenation. Finally, I have explored alternative strategies for managing thrombocytopenia. Platelets for transfusion are often not kept in rural and regional areas. I have shown through in vitro and transfusion studies that cryoprecipitate improves whole blood haemostasis in thrombocytopenia and should be considered as an option in bleeding patients unable to access platelet transfusions. Cryoprecipitate may be more effective than cryopreserved platelets currently under investigation. These results highlight the continuing role for research into novel ways to monitor and appropriate target treatment for the blood. They support the concept of research being included amongst a revised model of patient blood management

A Systems Analysis Approach to Understanding the Physiological Adaptation to Spaceflight

This book is a summary of interdisciplinary research (physiology, space medicine, engineering, computer science, mathematics) that spans two decades (1972-1992). The research was an attempt to use systems analysis, mathematical modeling, computer simulations, and database systems to integrate the biomedical spaceflight data that was being collected during this period. The goal of the effort was to achieve a better understanding of the human physiological response to short-term and long-term space travel. The activity was primarily devoted to analyzing the biomedical results of Skylab (1973-74), a series of three space missions which is still ranked as the most comprehensive of all long-term biomedical space studies to date. This work was begun as a coordinated effort between the National Aeronautics and Space Administration (Johnson Space Center) and the General Electric Companys Space Division (Houston, TX). It was the intent that this multidisciplined, integrative approach could reveal aspects of the then-new science of microgravity adaptation that were not obvious by adhering to the traditional methodology of examining each organ system in isolation. Some joint work with the Russians, including the Apollo-Soyez test project and a joint bedrest study was also supported during this period. In the 1980s the systems analysis groups effort was redirected to support the science management of human and animal experiments on the Space Shuttle. A few examples from this era are also included in the book. Parts of this work have been published elsewhere, presented at technical meetings, and documented in reports with limited distribution. These publications will be referenced throughout the text and the interested reader is advised to use these as resource material where additional details are desired. The intent of this book is not to reproduce these documents but rather to present a coherent view of the integrative analysis under one cover. This volume contains the first detailed publication (other than in internal reports) of an extensive metabolic balance analysis of Skylab data, the development and validation of the Whole-Body Algorithm, and simulation studies of diverse hypogravic environments. An analysis of cardiovascular deconditioning and a description of the calcium regulatory model are also new. A long period has passed between the completion of the main body of work represented in this book and its publication in this form. It was inevitable that new research efforts would lead to developments related to the spaceflight problems addressed and thereby make some of our biomedical conclusions obsolete. Although in some cases reference to more recent work have been included, for the most part this book should be considered an historical summary demonstrating the approach and utility of systems analysis and computer modeling in the NASA Life Sciences program at the time the studies were conducted