Pharmacokinetics with R

책 소개

Pharmacokinetics describes what the body does to a drug; pharmacodynamics describes what

the drug does to the body. Applying either requires quantitative answers. What steady-state

peak and trough concentrations result when a drug with a 12-hour half-life is given as 200 mg

every 8 hours? Does doubling the dose double exposure? This book uses R to work through

questions such as these.

The approach is to translate equations into code and examine the calculations.

Pharmacokinetic formulas are written as R functions, plotted and checked numerically.

Changing their assumptions allows the reader to explore nonlinear kinetics, flip-flop and

multiple compartments. The code printed in the text comes directly from En/R/snippets/;

the console output and figures were generated by running those files.

Several features of the book reflect this approach.

The calculations are worked out explicitly. The examples reproduce the computations

performed by NONMEM® in R. The objective functions for FO, FOCE-I and Laplacian

estimation are compared numerically with the software’s output. The UCP logistic transformation,

Cholesky parameterization and sandwich estimator are developed in equations and

code. These details help readers investigate unexpected results.

Results are checked by independent methods. Analytic solutions are compared

with numerical solutions, direct calculations with package results, and closed-form expressions

with simulations. Simulated data provide a further check because the generating values

are known. These comparisons test both the derivation and its implementation.

Methods are considered alongside regulation and practice. The text covers the

2026 US FDA bioequivalence guidance and Potvin’s two-stage design, the FDA population

pharmacokinetics guidance and reporting conventions, and the shift from trough concentration

to AUC in vancomycin therapeutic drug monitoring. These examples connect the

calculations to their use in research and treatment.

The examples include building a TDM tool. Chapter 13 develops an algorithm

that uses population model output (θ, Ω, Σ) for individual dose adjustment. It connects the

forward model, MAP estimation, posterior uncertainty and target-based dose calculation.

The vancomycin example can be adapted to another drug, such as an aminoglycoside.

The preparatory chapters focus on the material used later. Chapters 1–4 introduce

the R, mathematics, statistics and nonlinear regression needed for the pharmacokinetic

examples. Further mathematical methods are introduced where they are applied.

iii

출처: 국립중앙도서관 출판예정도서 등록 정보(출판사 제출)

목차

Preface .............................................................................. iii

Notation and Abbreviations .......................................................... xiii

I Preparation .......................................................................... 1

1 R, Git, Markdown, AI ............................................................. 3

1.1 Getting started with R ..................................................... 3

1.2 How R works ................................................................ 4

1.3 Vectors and data types ..................................................... 5

1.4 Functions and control flow ................................................. 8

1.5 Data structures ........................................................... 10

1.6 Reshaping data ............................................................ 13

1.7 Reading and writing files ................................................. 15

1.8 Graphics .................................................................. 16

1.9 Random numbers and reproducibility ........................................ 18

1.10 Git: keeping a history ................................................... 19

1.11 Markdown: what was done, and why ......................................... 20

1.12 AI: fast, but verified ................................................... 21

1.13 Where this chapter is used later ......................................... 22

References .................................................................... 23

Exercises ..................................................................... 23

2 Mathematical Foundations ........................................................ 25

2.1 Numbers and error ......................................................... 25

2.2 Exponentials and logarithms ............................................... 27

2.3 Differential equations .................................................... 29

2.4 Matrices .................................................................. 33

2.5 Numerical analysis ........................................................ 36

2.6 Approximation: the Taylor expansion ....................................... 42

2.7 Where this chapter is used later .......................................... 44

References .................................................................... 45

Exercises ..................................................................... 46

3 Statistical Foundations ......................................................... 49

3.1 Distributions: why the log-normal ......................................... 49

3.2 Likelihood ................................................................ 54

3.3 Estimation and confidence intervals ....................................... 56

3.4 Tests, the p value, and 3.84 .............................................. 59

3.5 How random numbers are generated .......................................... 62

3.6 Assuming no distribution: resampling ...................................... 64

3.7 Least squares: the archetype of regression ................................ 65

3.8 Where this chapter is used later .......................................... 66

References .................................................................... 67

Exercises ..................................................................... 68

4 Nonlinear Regression ............................................................ 71

4.1 Data and model ............................................................ 71

4.2 The objective function: what is minimized ................................. 72

4.3 Geometry: the expectation surface and the tangent plane ................... 74

4.4 Weights and the error model ............................................... 76

4.5 Initial estimates ......................................................... 78

4.6 Uncertainty: standard errors and confidence intervals ..................... 80

4.7 Reparameterization: the same model in other coordinates ................... 83

4.8 Diagnostics: the two signals the residuals send ........................... 85

4.9 Model selection and identifiability ....................................... 88

4.10 Where this chapter is used later ......................................... 94

References .................................................................... 94

Exercises ..................................................................... 95

II Pharmacokinetics ................................................................... 99

5 Introduction to Pharmacokinetics ............................................... 101

5.1 Pharmacokinetics after a single dose ..................................... 103

5.2 Pharmacokinetics under repeated dosing and constant infusion ............. 108

5.3 Compartmental models of drug disposition ................................. 113

5.4 Factors that influence pharmacokinetic processes ......................... 114

5.5 Pharmacokinetic linearity and nonlinearity ............................... 115

5.6 Dose proportionality ..................................................... 120

5.7 Drug interactions ........................................................ 124

References ................................................................... 124

Exercises .................................................................... 125

6 ADME ........................................................................... 127

6.1 Absorption ............................................................... 127

6.2 Distribution ............................................................. 135

6.3 Metabolism ............................................................... 140

6.4 Excretion ................................................................ 148

References ................................................................... 151

Exercises .........................................................

출처: 국립중앙도서관 ISBN 서지정보(출판사 제출)

서지 풀이

부가기호 95510: 독자 대상 전문 · 발행 형태 전자출판물 · 내용 분류 기술과학.

출처: 국립중앙도서관 ISBN 서지정보 · 부가기호 뜻은 국립중앙도서관 ISBN 안내 기준

서점에서 확인

아직 서점 판매가 확인되지 않았습니다. 판매가 확인되면 이 자리에 구매 버튼이 생깁니다. 위의 출간 알림을 신청하시면 출간일에 서점 링크를 메일로 보내 드립니다.

먼저 찾아보기(결과가 없을 수 있음): 교보문고 · 예스24 — 서점 링크는 제휴 링크입니다.

자주 묻는 질문

『Pharmacokinetics with R』의 출간일은 언제인가요?

주식회사 에이씨씨티에서 2026-12-01 출간 예정입니다 (국립중앙도서관 ISBN 서지정보 기준). ISBN 9791122258752.

『Pharmacokinetics with R』의 저자와 출판사는?

Kyun-Seop Bae / 주식회사 에이씨씨티. 출간 후 상세 정보가 갱신됩니다.

『Pharmacokinetics with R』은 전자책·오디오북으로도 나오나요?

전자책으로 출간 예정입니다. (국립중앙도서관 출판예정도서 등록 기준이며, 별도 판형이 추가될 수 있습니다.)

같은 출판사의 다른 출간 예정

Scientific Inference in Clinical Trials with R (2026-12-01)

과학 계산 with R (2026-11-21)

과학 계산 with R (2026-11-21)

계량약리학 with NONMEM and R (2026-11-11)

기술과학 분야 · 비슷한 시기 출간 예정

Migraña AQUÍ Y AHORA 리쉐북스 · 2026-12-01

나는 그렇게 욕실 시공자가 되었다 위바르 · 2026-12-01

[실물] 시하끝하 전기기사 필기 유형별 기출문제집_전기설비기술기준 하이에듀 · 2026-12-01

(답이보인다) 30일 단기완성 전기기사 ⋅ 산업기사 필기 (2027) 동일출판사 · 2026-12-01

2026-12-01 출간 예정 전체

2026-12-01 출간 예정 도서 전체 보기 · 출간 예정 캘린더

이 책은 국립중앙도서관 ISBN 서지정보에 출간예정으로 등록된 도서입니다. 서점 등재 전 단계의 공식 서지 정보이며, 출간 후 소개·표지 등 상세 정보가 자동으로 갱신됩니다.

출처: 국립중앙도서관 서지정보유통지원시스템 (매일 갱신)